{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Importing Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set(style='dark')\n",
    "\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = pd.read_csv(path + \"\\\\Train.csv\")\n",
    "test = pd.read_csv(path+\"\\\\Test.csv\")\n",
    "sample_sub = pd.read_csv(path+\"\\\\sample_submission.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((29451, 12), (68720, 11), (68720, 1))"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.shape, test.shape, sample_sub.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## Data Description"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### POSTED_BY - Category marking who has listed the property\n",
    "\n",
    "UNDER_CONSTRUCTION - Under Construction or Not\n",
    "\n",
    "RERA - Rera approved or Not\n",
    "\n",
    "BHK_NO - Number of Rooms\n",
    "\n",
    "BHK_OR_RK - Type of property\n",
    "\n",
    "SQUARE_FT - Total area of the house in square feet\n",
    "\n",
    "READY_TO_MOVE - Category marking Ready to move or Not\n",
    "\n",
    "RESALE - Category marking Resale or not\n",
    "\n",
    "ADDRESS - Address of the property\n",
    "\n",
    "LONGITUDE - Longitude of the property\n",
    "\n",
    "LATITUDE - Latitude of the property\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hypothesis Generation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Does house price is more when dealer is posting?\n",
    "2. Does Under_Construction houses have less price?\n",
    "3. Does RERA approved houses have more price?\n",
    "4. Houses with greater number of rooms have more price.\n",
    "5. Higher the square_ft higher the price.\n",
    "6. Resale 1 have perticularly less price."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# EDA\n",
    "\n",
    "Lets go and explore our training and test datasets. We will do the following steps:\n",
    "\n",
    "1. Brief Look at the Dataset\n",
    "2. See the shape of Dataset. Variables and Target column\n",
    "3. Target Distribution\n",
    "4. See the variables datatypes\n",
    "5. See The Number/Percentage Of Missing values\n",
    "6. Unique Values in each Variable"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Brief Look at the Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>POSTED_BY</th>\n",
       "      <th>UNDER_CONSTRUCTION</th>\n",
       "      <th>RERA</th>\n",
       "      <th>BHK_NO.</th>\n",
       "      <th>BHK_OR_RK</th>\n",
       "      <th>SQUARE_FT</th>\n",
       "      <th>READY_TO_MOVE</th>\n",
       "      <th>RESALE</th>\n",
       "      <th>ADDRESS</th>\n",
       "      <th>LONGITUDE</th>\n",
       "      <th>LATITUDE</th>\n",
       "      <th>TARGET(PRICE_IN_LACS)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Owner</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>BHK</td>\n",
       "      <td>1300.236407</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Ksfc Layout,Bangalore</td>\n",
       "      <td>12.969910</td>\n",
       "      <td>77.597960</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Dealer</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>BHK</td>\n",
       "      <td>1275.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Vishweshwara Nagar,Mysore</td>\n",
       "      <td>12.274538</td>\n",
       "      <td>76.644605</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Owner</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>BHK</td>\n",
       "      <td>933.159722</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Jigani,Bangalore</td>\n",
       "      <td>12.778033</td>\n",
       "      <td>77.632191</td>\n",
       "      <td>43.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Owner</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>BHK</td>\n",
       "      <td>929.921143</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sector-1 Vaishali,Ghaziabad</td>\n",
       "      <td>28.642300</td>\n",
       "      <td>77.344500</td>\n",
       "      <td>62.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Dealer</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>BHK</td>\n",
       "      <td>999.009247</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>New Town,Kolkata</td>\n",
       "      <td>22.592200</td>\n",
       "      <td>88.484911</td>\n",
       "      <td>60.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  POSTED_BY  UNDER_CONSTRUCTION  RERA  BHK_NO. BHK_OR_RK    SQUARE_FT  \\\n",
       "0     Owner                   0     0        2       BHK  1300.236407   \n",
       "1    Dealer                   0     0        2       BHK  1275.000000   \n",
       "2     Owner                   0     0        2       BHK   933.159722   \n",
       "3     Owner                   0     1        2       BHK   929.921143   \n",
       "4    Dealer                   1     0        2       BHK   999.009247   \n",
       "\n",
       "   READY_TO_MOVE  RESALE                      ADDRESS  LONGITUDE   LATITUDE  \\\n",
       "0              1       1        Ksfc Layout,Bangalore  12.969910  77.597960   \n",
       "1              1       1    Vishweshwara Nagar,Mysore  12.274538  76.644605   \n",
       "2              1       1             Jigani,Bangalore  12.778033  77.632191   \n",
       "3              1       1  Sector-1 Vaishali,Ghaziabad  28.642300  77.344500   \n",
       "4              0       1             New Town,Kolkata  22.592200  88.484911   \n",
       "\n",
       "   TARGET(PRICE_IN_LACS)  \n",
       "0                   55.0  \n",
       "1                   51.0  \n",
       "2                   43.0  \n",
       "3                   62.5  \n",
       "4                   60.5  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>POSTED_BY</th>\n",
       "      <th>UNDER_CONSTRUCTION</th>\n",
       "      <th>RERA</th>\n",
       "      <th>BHK_NO.</th>\n",
       "      <th>BHK_OR_RK</th>\n",
       "      <th>SQUARE_FT</th>\n",
       "      <th>READY_TO_MOVE</th>\n",
       "      <th>RESALE</th>\n",
       "      <th>ADDRESS</th>\n",
       "      <th>LONGITUDE</th>\n",
       "      <th>LATITUDE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Owner</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>BHK</td>\n",
       "      <td>545.171340</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Kamrej,Surat</td>\n",
       "      <td>21.262000</td>\n",
       "      <td>73.047700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Dealer</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>BHK</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Panvel,Lalitpur</td>\n",
       "      <td>18.966114</td>\n",
       "      <td>73.148278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dealer</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>BHK</td>\n",
       "      <td>1257.096513</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>New Town,Kolkata</td>\n",
       "      <td>22.592200</td>\n",
       "      <td>88.484911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Dealer</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>BHK</td>\n",
       "      <td>1400.329489</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Kalwar Road,Jaipur</td>\n",
       "      <td>26.988300</td>\n",
       "      <td>75.584600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Owner</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>BHK</td>\n",
       "      <td>430.477830</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mai Mandir,Nadiad</td>\n",
       "      <td>22.700000</td>\n",
       "      <td>72.870000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  POSTED_BY  UNDER_CONSTRUCTION  RERA  BHK_NO. BHK_OR_RK    SQUARE_FT  \\\n",
       "0     Owner                   0     0        1       BHK   545.171340   \n",
       "1    Dealer                   1     1        2       BHK   800.000000   \n",
       "2    Dealer                   0     0        2       BHK  1257.096513   \n",
       "3    Dealer                   0     0        3       BHK  1400.329489   \n",
       "4     Owner                   0     0        1       BHK   430.477830   \n",
       "\n",
       "   READY_TO_MOVE  RESALE             ADDRESS  LONGITUDE   LATITUDE  \n",
       "0              1       1        Kamrej,Surat  21.262000  73.047700  \n",
       "1              0       0     Panvel,Lalitpur  18.966114  73.148278  \n",
       "2              1       1    New Town,Kolkata  22.592200  88.484911  \n",
       "3              1       1  Kalwar Road,Jaipur  26.988300  75.584600  \n",
       "4              1       1   Mai Mandir,Nadiad  22.700000  72.870000  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>UNDER_CONSTRUCTION</th>\n",
       "      <td>29451.0</td>\n",
       "      <td>0.179756</td>\n",
       "      <td>3.839908e-01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RERA</th>\n",
       "      <td>29451.0</td>\n",
       "      <td>0.317918</td>\n",
       "      <td>4.656753e-01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BHK_NO.</th>\n",
       "      <td>29451.0</td>\n",
       "      <td>2.392279</td>\n",
       "      <td>8.790913e-01</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SQUARE_FT</th>\n",
       "      <td>29451.0</td>\n",
       "      <td>19802.170190</td>\n",
       "      <td>1.901335e+06</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>900.021130</td>\n",
       "      <td>1175.056750</td>\n",
       "      <td>1550.688124</td>\n",
       "      <td>2.545455e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>READY_TO_MOVE</th>\n",
       "      <td>29451.0</td>\n",
       "      <td>0.820244</td>\n",
       "      <td>3.839908e-01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RESALE</th>\n",
       "      <td>29451.0</td>\n",
       "      <td>0.929578</td>\n",
       "      <td>2.558613e-01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LONGITUDE</th>\n",
       "      <td>29451.0</td>\n",
       "      <td>21.300255</td>\n",
       "      <td>6.205306e+00</td>\n",
       "      <td>-37.713008</td>\n",
       "      <td>18.452663</td>\n",
       "      <td>20.750000</td>\n",
       "      <td>26.900926</td>\n",
       "      <td>5.991288e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LATITUDE</th>\n",
       "      <td>29451.0</td>\n",
       "      <td>76.837695</td>\n",
       "      <td>1.055775e+01</td>\n",
       "      <td>-121.761248</td>\n",
       "      <td>73.798100</td>\n",
       "      <td>77.324137</td>\n",
       "      <td>77.828740</td>\n",
       "      <td>1.529627e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TARGET(PRICE_IN_LACS)</th>\n",
       "      <td>29451.0</td>\n",
       "      <td>142.898746</td>\n",
       "      <td>6.568807e+02</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>3.000000e+04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         count          mean           std         min  \\\n",
       "UNDER_CONSTRUCTION     29451.0      0.179756  3.839908e-01    0.000000   \n",
       "RERA                   29451.0      0.317918  4.656753e-01    0.000000   \n",
       "BHK_NO.                29451.0      2.392279  8.790913e-01    1.000000   \n",
       "SQUARE_FT              29451.0  19802.170190  1.901335e+06    3.000000   \n",
       "READY_TO_MOVE          29451.0      0.820244  3.839908e-01    0.000000   \n",
       "RESALE                 29451.0      0.929578  2.558613e-01    0.000000   \n",
       "LONGITUDE              29451.0     21.300255  6.205306e+00  -37.713008   \n",
       "LATITUDE               29451.0     76.837695  1.055775e+01 -121.761248   \n",
       "TARGET(PRICE_IN_LACS)  29451.0    142.898746  6.568807e+02    0.250000   \n",
       "\n",
       "                              25%          50%          75%           max  \n",
       "UNDER_CONSTRUCTION       0.000000     0.000000     0.000000  1.000000e+00  \n",
       "RERA                     0.000000     0.000000     1.000000  1.000000e+00  \n",
       "BHK_NO.                  2.000000     2.000000     3.000000  2.000000e+01  \n",
       "SQUARE_FT              900.021130  1175.056750  1550.688124  2.545455e+08  \n",
       "READY_TO_MOVE            1.000000     1.000000     1.000000  1.000000e+00  \n",
       "RESALE                   1.000000     1.000000     1.000000  1.000000e+00  \n",
       "LONGITUDE               18.452663    20.750000    26.900926  5.991288e+01  \n",
       "LATITUDE                73.798100    77.324137    77.828740  1.529627e+02  \n",
       "TARGET(PRICE_IN_LACS)   38.000000    62.000000   100.000000  3.000000e+04  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>UNDER_CONSTRUCTION</th>\n",
       "      <td>68720.0</td>\n",
       "      <td>0.176557</td>\n",
       "      <td>0.381296</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RERA</th>\n",
       "      <td>68720.0</td>\n",
       "      <td>0.316531</td>\n",
       "      <td>0.465126</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BHK_NO.</th>\n",
       "      <td>68720.0</td>\n",
       "      <td>2.388198</td>\n",
       "      <td>0.864577</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.100000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SQUARE_FT</th>\n",
       "      <td>68720.0</td>\n",
       "      <td>2762.418558</td>\n",
       "      <td>164099.148524</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>900.031031</td>\n",
       "      <td>1174.981923</td>\n",
       "      <td>1550.264643</td>\n",
       "      <td>4.016393e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>READY_TO_MOVE</th>\n",
       "      <td>68720.0</td>\n",
       "      <td>0.823443</td>\n",
       "      <td>0.381296</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RESALE</th>\n",
       "      <td>68720.0</td>\n",
       "      <td>0.933498</td>\n",
       "      <td>0.249159</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LONGITUDE</th>\n",
       "      <td>68720.0</td>\n",
       "      <td>21.288045</td>\n",
       "      <td>6.179034</td>\n",
       "      <td>-38.391261</td>\n",
       "      <td>18.452663</td>\n",
       "      <td>20.933260</td>\n",
       "      <td>26.888396</td>\n",
       "      <td>6.518333e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LATITUDE</th>\n",
       "      <td>68720.0</td>\n",
       "      <td>76.919388</td>\n",
       "      <td>10.100950</td>\n",
       "      <td>-118.354100</td>\n",
       "      <td>73.798100</td>\n",
       "      <td>77.324966</td>\n",
       "      <td>78.000723</td>\n",
       "      <td>1.752780e+02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      count         mean            std         min  \\\n",
       "UNDER_CONSTRUCTION  68720.0     0.176557       0.381296    0.000000   \n",
       "RERA                68720.0     0.316531       0.465126    0.000000   \n",
       "BHK_NO.             68720.0     2.388198       0.864577    1.000000   \n",
       "SQUARE_FT           68720.0  2762.418558  164099.148524    1.000000   \n",
       "READY_TO_MOVE       68720.0     0.823443       0.381296    0.000000   \n",
       "RESALE              68720.0     0.933498       0.249159    0.000000   \n",
       "LONGITUDE           68720.0    21.288045       6.179034  -38.391261   \n",
       "LATITUDE            68720.0    76.919388      10.100950 -118.354100   \n",
       "\n",
       "                           25%          50%          75%           max  \n",
       "UNDER_CONSTRUCTION    0.000000     0.000000     0.000000  1.000000e+00  \n",
       "RERA                  0.000000     0.000000     1.000000  1.000000e+00  \n",
       "BHK_NO.               2.000000     2.000000     3.000000  3.100000e+01  \n",
       "SQUARE_FT           900.031031  1174.981923  1550.264643  4.016393e+07  \n",
       "READY_TO_MOVE         1.000000     1.000000     1.000000  1.000000e+00  \n",
       "RESALE                1.000000     1.000000     1.000000  1.000000e+00  \n",
       "LONGITUDE            18.452663    20.933260    26.888396  6.518333e+01  \n",
       "LATITUDE             73.798100    77.324966    78.000723  1.752780e+02  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.describe().T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. See the shape of Dataset. Variables and Target column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The shape of Train Dataset is (29451, 12)\n",
      "The shape of Test Dataset is (68720, 11)\n",
      "\n",
      "The Dataset have total 11 features\n"
     ]
    }
   ],
   "source": [
    "print(f'The shape of Train Dataset is {train.shape}')\n",
    "print(f'The shape of Test Dataset is {test.shape}')\n",
    "\n",
    "target = 'TARGET(PRICE_IN_LACS)' # Target Variable\n",
    "\n",
    "features = [col for col in train.columns if col not in [target]] # Features\n",
    "\n",
    "print(f'\\nThe Dataset have total {len(features)} features')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Target Distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TARGET(PRICE_IN_LACS)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>29451.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>142.898746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>656.880713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>38.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>62.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>30000.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       TARGET(PRICE_IN_LACS)\n",
       "count           29451.000000\n",
       "mean              142.898746\n",
       "std               656.880713\n",
       "min                 0.250000\n",
       "25%                38.000000\n",
       "50%                62.000000\n",
       "75%               100.000000\n",
       "max             30000.000000"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(train[target].describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1ef2c735c08>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f,ax = plt.subplots(2,1,figsize=(20,10))\n",
    "axx = ax.flatten()\n",
    "\n",
    "sns.distplot(train[target],ax = axx[0], color='Red')\n",
    "sns.boxplot(train[target],ax = axx[1], color='Blue')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* We have highly left skewed data in target variable."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. See the variables datatypes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 29451 entries, 0 to 29450\n",
      "Data columns (total 12 columns):\n",
      " #   Column                 Non-Null Count  Dtype  \n",
      "---  ------                 --------------  -----  \n",
      " 0   POSTED_BY              29451 non-null  object \n",
      " 1   UNDER_CONSTRUCTION     29451 non-null  int64  \n",
      " 2   RERA                   29451 non-null  int64  \n",
      " 3   BHK_NO.                29451 non-null  int64  \n",
      " 4   BHK_OR_RK              29451 non-null  object \n",
      " 5   SQUARE_FT              29451 non-null  float64\n",
      " 6   READY_TO_MOVE          29451 non-null  int64  \n",
      " 7   RESALE                 29451 non-null  int64  \n",
      " 8   ADDRESS                29451 non-null  object \n",
      " 9   LONGITUDE              29451 non-null  float64\n",
      " 10  LATITUDE               29451 non-null  float64\n",
      " 11  TARGET(PRICE_IN_LACS)  29451 non-null  float64\n",
      "dtypes: float64(4), int64(5), object(3)\n",
      "memory usage: 2.7+ MB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5. See The Number/Percentage Of Missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.isna().sum().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.isna().sum().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6. Unique Values in each Variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>POSTED_BY</th>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNDER_CONSTRUCTION</th>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RERA</th>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BHK_NO.</th>\n",
       "      <td>16</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BHK_OR_RK</th>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SQUARE_FT</th>\n",
       "      <td>19561</td>\n",
       "      <td>37704.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>READY_TO_MOVE</th>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RESALE</th>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADDRESS</th>\n",
       "      <td>6899</td>\n",
       "      <td>11048.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LONGITUDE</th>\n",
       "      <td>4087</td>\n",
       "      <td>5907.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LATITUDE</th>\n",
       "      <td>4078</td>\n",
       "      <td>5914.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TARGET(PRICE_IN_LACS)</th>\n",
       "      <td>1172</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           0        1\n",
       "POSTED_BY                  3      3.0\n",
       "UNDER_CONSTRUCTION         2      2.0\n",
       "RERA                       2      2.0\n",
       "BHK_NO.                   16     17.0\n",
       "BHK_OR_RK                  2      2.0\n",
       "SQUARE_FT              19561  37704.0\n",
       "READY_TO_MOVE              2      2.0\n",
       "RESALE                     2      2.0\n",
       "ADDRESS                 6899  11048.0\n",
       "LONGITUDE               4087   5907.0\n",
       "LATITUDE                4078   5914.0\n",
       "TARGET(PRICE_IN_LACS)   1172      NaN"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat((train.nunique(), test.nunique()), axis = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* There is one Bhk_No is less in train than test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# Univariate Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Pie Plots for categorical Variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_ls = ['POSTED_BY', 'UNDER_CONSTRUCTION', 'RERA', 'BHK_NO.', 'BHK_OR_RK',\n",
    "       'READY_TO_MOVE', 'RESALE']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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V12so4GNMA4DSYNmObNvRjDnrNfmL1bREOw6S4n26YsCJ6tO5kbxeQx6eO6IUUbg5DvJ6/jv6bMEm/eezlcrMiUQ7pEqnUe0qGjG0nVo1rsb+NwBwDMIRW+GIrTc+Wq4vF29h9lYUnNqurkYMaaekBB9jGgAcg9yQpczssMZPWaIlq3dHO5xKJyHOq2HntNY53ZvI6zHkoUsCAJRYMGxp+fq9enHqUu1Kz412OJVOg1pJuuHPJ6tFA7okoPRQuCljwbClfQeCemTCIm3YzibN0dajXV3d+JcO8vtM+bwsYwSA4giGLS3+daeen7pU2blMQogmr8fUFQNaa0CPZvL7TBkG+98AQFFFLEeW5WjCzF/137kbmYQQZfVqJOr6P5/MJDsAKIHckKXMnLCem7RES9cwCSHaOrWupRsuPEVVmGSHUkDhpozkr7L5YPZavffZKtkkAzEjOdGvm/7SQe1b1KAKDgBFEI7YCoVtPf2fH7Voxc5oh4PfOaFhiu68oouSk/wkBgBQBMGQpRWb9umpd3/U/qxQtMPB73RvW1c3XdxBAa8pH3sFAMAR5T13tPXe56v1wTdree4YQ3xeU5f3P1EDejSR3+dhkh1KjMJNGQiGLO3NCOqRtxdpYxqrbGJVz/b1NPIvp8jvZfUNABxOMGxp4fIdenHaz6yyiVE+r6krBpyo/qc2VcDPeAYAh2LbjiKWo1en/6LPF26Odjg4jOREv2686BSdfEJNJtkBwGEEw5b2Z4b0zzcX8twxhp3QMEWjruiilKQAeRpKhMJNKcqvdr//zTpN+pxVNuVB1SS/br64o9o2q05iAAC/E47YCoZtPTXxB/2wcle0w0ERtGpUTaOu6Kwqiay+AYDfC4YsbdmVqUfeXkTf/3Ki1yn1NPKiDvJ7Tfa+AYDfCYUtfbFws/710XJFLCfa4eAofF5TV5/fVn26NCRHQ7FRuCklobClPQdYZVNenXZKPY288BQFfB4SAwCVXjBkadGKnXphyhJlB61oh4Ni8HtN/d95bXRO98YKkBgAqOTyJ9ZNnLVKH8xeKzLf8qVmSrzuurKrGtZKYpIdgEovbNkKhmw99s5i9rIph05pWVN3XNZZcQEPXX9QZBRuSkEwZOmHlTv11MQfFabaXW7VSInTgyN6qGa1BJYwAqi0QmFbr07/RZ8t2BTtUHAMOrSqqTuv6KI4v1emSU9lAJVPOGIrIzus+16bp007MqMdDkrINKRh556owac3Y0ICgEorGLL0y7o9emrij8qifXW5lZzo15iruqtx3SqsvkGRULg5RqGwpfc+X6WpX62NdigoBQGfR7df1omeygAqHdt2lBu29MDrC7Ri475oh4NSUK9Gov55XU8lJ/rlZ5NnAJVIMGRp1eZ0PfzWQlaOVhCntqurWy7pqICfTZ4BVC48d6xYPKaha4e2U+/OtE7D0VEdT45/AAAgAElEQVS4KSHHcRWK2Hp0wiJ6/1dAl/RrpT/1bsGsLgCVQihsa/f+HI15ZZ5276f3f0WSGOfVvVd1U/P6KUxIAFApBMOWPpyzXv/+dAWt0SqYJnWT9cC1pyop3kebGQAVnuM4CoZtPTJhkX5aRWu0iubsro00Ymg7ijc4Igo3JZC/7H70y3O1bXdWtMNBGel2Uh3dNqwTs7oAVGjBkKWla3br8X//oFDEjnY4KAOmIV0zpJ36dm1EYgCgQguGLT076Sd9t2R7tENBGUlO9Gvs1d3VqA5tZgBUXJGIrQPZYd390vdK25Md7XBQRlo1qqax13RXfMArL/tt4xAo3BRTMGRp7db9GvfGApbdVwKN61TRg3/rwawuABVSKGxpypdrNOmL1dEOBcdB3y4Nde0F7XnQBaDCsW1HOUFLY1+bpzVb9kc7HJQxj2no+j+11+kdGzCmAahwgmFLm3dkauyr89jPphJITY7T/SNOVd0aiQrQ3hp/QOGmGIIhS18s2qzXpv8ih+9apZE/q6txnSq0TgNQYQTDlh57Z7EW/boz2qHgOGrVuJruu6a7EgI+mSarSQGUf5btKCMrrNvGz9HudNp9ViYX9G6hS/q1ongDoMIIhiwtXrlTT777gyybB4+VRcDn0f0jTlWLBikK+Cne4H8o3BRRMGzp/a/X6j+frYp2KIgCn9fU2Ku7q3XjahRvAJR7uSFLY1+dpxUb90U7FERB3RqJenxkLyUl+OQxWZIPoPyKWI7SM4K6ffy32pcRjHY4iILzejbVlQPbULwBUO4FQ5a+/3m7np30E3u0VUJej6kxV3XTiU1TGdNQgMJNEQTDlv4za5Xe/2ZttENBFHk9hu4Z3k1tm1fnhyiAcsl1XeWGLI1+eS6tZCq52qkJeuLGXqqS4JeHfsoAyqGIZWtXeq7uGP+tMrLD0Q4HUdS3ayP9bWg7JtgBKLeCIUuzf9yq56cujXYoiCKPaWjUFV3UoWVNxQUY00Dh5qhCYUtvffKrPv5uQ7RDQQwwTUOjLu+sjq1rUbwBUK64rqucoKW7XvxOG7ZnRDscxICaKfF6/MZeqpoUYDNMAOVKOGJr+55s3fnCd8qm/z8knd6hvm686BSKNwDKnfxtGV754Jdoh4IYYBrSPy7pqO5t61K8AYWbIwmGLb398a/6+HuKNvgf05Du/L+u6tCqJsUbAOVGTjCiUc9/p41pFG3wP6nJcXr65jNUNYmVNwDKh1DE1uYdGbrnpbnKDVnRDgcxpHvbOrptWGf2BwBQbgRDlmbO26g3Ploe7VAQQwxDuu6C9urdqSHFm0qODP0wgmFL7366kqINDuK40qMTFmn5+r0KhkkWAcS+3JClu1/6nqINDrIvI6jbxs9RZm5EjuNEOxwAOKKIZWvrzkzd9cL3FG1wkPnLduiRCYsUIkcDUA4Ew5Y++m49RRscxHWlF6f9rDk/bVWQ33cqNQo3hxAMW5ryxWpNn70u2qEgRtmOq3FvLNCazftJDADEtNyQpXtfnqt1Ww9EOxTEqN3pubrjuW+VlWvJcViIDSA22Y6j9IyQRr88V6GIHe1wEKMWr9ipVz74hQl2AGJaMGTp6x+2asJ/V0Q7FMSwF6Yu1fINe3nuWIlRuPmDYMjSZ/M3afKXa6IdCmKcZbsa+9o8bd2VpYjFLGUAsScUtjXujQVatTk92qEgxqXtzdao57/lQReAmJS/T9udL36nLPa0wVF8vnCzps9exyxlADEpFLG1YuM+vTxtabRDQYxzXOmhNxdq6+4sRSwmrVRGFG5+JxyxtXpzuv714bJoh4JyImI5GvvaPGUHI2K7KACxJBiy9NbHy/Xz2j3RDgXlxNZdWbSYARCTgmFb97z0vXan50Y7FJQT7366UnN/2c6EBAAxxbId7dibrX++uVAsdEdRhC1Ho1+aq/TMkGybSeOVDYWb3ziOo/2ZIY3jhyeK6UBWWGNeoWUDgNgRDFv6buk29mlDsf20arcmzlrFLGUAMSMUtvTQWwu1YTv7tKF4np20RKs3pZOnAYgJjuMqMyes0S/x/AjFk5Ub0Z0vfKecoMWk8UqGws1vgmFbo1+eyyaXKJEN2zP0zHs/MksZQNRFLFubd2Tq+SksvUfJvP/NWi1asVOhMAklgJLJysrSwIEDtXXr1mM6TzBs6cWpS7Vk9e5SigyVieO4euCNBdq5N1sWs5QBRFkwbOnuF7/X/qxQtENBObQ7PVd3v/S9guRolQqFG+XtAfDPtxYqbW92tENBOfb90jTN+HY9s5QBRE3eLK6I7n99vmyWj+IYPP2fH7V9D72UARTf0qVLdckll2jjxo3HdJ5g2NJnCzbpqx+OrfiDyi302wRNcjQAJVFaExFCYVsP/muBtu7KKqXIUBltTMvQUxN/pA1oJVLpCzfBsKW3/7tcP69hDwAcu3/PXKHlG/YySxlAVIQjtu59ea4yssPRDgXlXMRyNPbVecoNMZ4BKJ7Jkydr7NixqlWrVonPYduO0vZk640Pl5diZKis0n9riU6OBqA4SmsiQm7I0qQvVmnZ+r2lExgqtfnL0jRr3iaKN5VEpS7cBMOWvl+6XR99yx4AKB2uKz3y9iLtywjKdliOD+D4CYUtPfbOYm3emRntUFBBpGeGNPbVeSQFAIrln//8pzp37nxM5whFbD3wL1aPovQsX79X732+itboAIqsNCYiRCxH67ft19Sv1pRiZKjs3vh4uTbv+H/27js8qjJ9H/h9ztT0CQQCoTfpRJAqzRURkY66FtZ1V1FBd139rm1tqys/266iK4qirmJHUUAQKyiIIAICgUBIKIEE0kgv086c8/sjEIkEEmDmvGfO3J/r8tpkMnDuLMk8c97yvJVsAxoBInbiRlU1FJbUYN7H20RHIZOpPS/pR/j8fAElIn14vAqWrd2PTbsLREchk9mbW4b5n6SxxQwR6cZzbCHC0TKP6ChkMotXZyHzUCnbgBJRkwRjIYLHp+DJhZvA8+QpmFRVw//jTtKIELETN35FxVNvb4YS4KsnBV9hqRsLlqRxRRcRhZyqaigu9+D9rzJERyGTWr05B+kHiuFXuCCBiELL41Pw5YZsbMkoFB2FTOqZdzazDSgR6cLrU/DUwk0or2Ibawq+kgoP/v3uZnjZHcHUInLixuNV8OE3e5DDdjIUQt9uykFWTim3LhJRSNUuRNjEdjIUUs9/sJUrlIkopAIBFYeLqvDWil2io5CJVVT78NTCTRzoIqKQ8ngVLP9hP9L28jxtCp0tGYX4aiPPuzGziJu4UVUV+cXV+PQ79pek0Hv2vV+4QpmIQsbjU/DJ6ixk51WIjkImV1blxUuLt7NlGhGFjD+g4ok3f+ZCBAq5HfuO4pufD7HFDBGFREBVkVtUhXe+ZEcECr03l+9CZTV3dZlVxE3cHG+RxvsB0kNJhQevLuHZAEQUfKqqoajUjUWrMkVHoQixduthpO8v5s4bImqS1atXo23btk16rtur4J2Vu1FY6g5xKqJaCz/fBTdXKBNRCCiKimfe3gyVA4+kAyWg4j/vbeGuG5OKqIkbj1fBe19l4HBRlegoFEFWbcpBJlumEVGQ+ZUAnlq4iTcEpKvnP9zKnaREFFSqqiLvaDWWr9svOgpFEI8vgOc/+IUL7IioUWe6EOGjbzORV1wd4lREv9p1oATr047A5+cCO7OJmImbgFrbM3nZmn2io1AEYss0Igomj1fBR6uycIhntZHOyqq8ePHjbRzoIhLs/vvvr/t4yZIl9b525ZVX6h3nnPgVDf9+dzM0rkMgnW3JKMT2rCLuJCUSzCw1TdM0lFZ68Ml3e0VHoQi0YMkOTtyYUMRM3CiKiqfZIo0EYcs0IgoWVdVQUFqDxat5VhuJsW7bEexkyzQiofbs2VP38dtvv13va4oSPu83PT4FK9btR24hOyKQGPMWb4cS4CABkUhmqWk+fwDPvvcLz2ojIao9ChfYmVBETNx4fQqWrt3PrYok1KpNOcgpqITG5YREdA78SgDPf7CVLdJIqP8u4s8gkUgnvp/87XtLSZL0jnPW3F4F73/Fw5tJnLJKL95YtgNuDnQRCWOGmuZTAli/Iw+Zh0pFR6EItj4tDxkHeVSDmUTExI0S0PAJVyaTAbyyZAe83LpIRGcpEFCxPeso9uaWiY5CEa600ovl6w7Ay0MwiYQLl0Gt33J7Fcz7eDt8bCdMgn398yHkF1dzgR2RAYRrTQsoGl5ftlN0DCL8d9FW7voyEdNP3Li9Ct77KoMraMgQMg+VIn1/MQIqb1CJ6MwpqobXP+MNARnDx6syeVNAJEi4DmydKL+4Gj+n54uOQQRNA175NA1eHxfYEYkQ7jXN41Xw7le7UVHtEx2FCEVlbnyz8SDPuzEJq+gAoebxKfhi/QHRMYjqvL5sJ57/v4tgMf20KREFk18JYO0vucg7yrafZAw1HgWLvsnENZd2R5TD9G8piQwlJycHs2bNOuljAMjNzRUVq8k8XgWvLtkhOgZRnV0HSrA3twy9OjWHLIf3IDJRuAn3muZTVHyxPlt0DKI6H3y9B5cMbi86BgWBpJl4P7Dbq+Clj7dhzdbDoqMQ1fP36wZgeGob2KycvSGipvH6FMx84luUVXpFRyGqY7PKeOuRSxEf4xAdhSiiLFmy5LRfnzZtmk5JzpyqatidXYL7X1onOgpRPV3aJODpv4yAw87FCER6Cuea5vYqeGtFOlZy4oYMZsZlPTBtdBfWtDBn6n+90goP1m7jpA0Zz1uf78KwvimiYxBRmPD6Ali+bj8nbchw/IqKN1fswi1T+3LXDZGO4uLiMGbMmLBsL+NXAnhtKXfbkPHsO1yOtL1HMaB7S1jYHoFIN+Fc07y+AL7eeFB0DKKTfPrdXkwe2Vl0DDpHpn034vEqeGVJGsy7n4jCWXG5B1/+lA0ve04SURMEVBUffZslOgZRg1ZvzkFlDXt6E+nphRdewJgxY7BgwQKUlJSIjtNkgYCKtL1Hse9wuegoRA363/J0KDy/jUhX4VrT3F4FC1fughLgawYZj9ur4IOv98DDM9/DmiknbjRNw8H8SmzdUyQ6CtEpffj1Hqi8KSCiRni8Ct7/KgNuvuEig1JVDa8t3cGfUSIdLV++HM8++ywOHDiA8ePH47777kNaWproWI1SVA1vfJYuOgbRKeUWVuGnHXlQFFV0FKKIEa41rcbjx+rNOaJjEJ3S5z8egE/hgvFwZsqJG48vgLdW8IaAjK3K7ceytfvg464bIjqNgKqxZzIZ3k8781FS7hEdgyii9O/fH08++SRWrVqFfv364ZFHHsEVV1yBpUuXio7WIFXVsC2zEIeLqkRHITqtd77YDZWtO4h0FW41ze1R8OaKXVyMS4bmV1Qs+iaTu27CmCknbkorPNi5v1h0DKJGfb7ugOgIRGRgXn8An/+4H36u+qQwsOjbPXB7/aJjEEWc2NhYzJgxA++++y4GDhyIBx54QHSkBnn9AXy8im0/yfgKSmqwO7sEGidviHQXLjXNpwTww9Zc0TGIGvXNz4cQhsdH0TGmm7hxexUs+jZTdAyiJimr8mJjej4CKgdliehkEoDlnOClMPHDtiNgOSPS36ZNm3DffffhkksuQUVFBRYtWiQ6UoOKyz3Yc7BUdAyiJlm8OgseHzsjEOktHGqa16fgsx/2gZttKBy4vQq+35ILJcAbtXBkFR0g2FRVw9qth0XHIGqyT1ZnYVCvZFjspptHJaJzEFBV/LwrH2WVXtFRiJpECahYvm4/pl3UFQ6bRXQcIlMrLCzEkiVL8MknnwAArr76avzjH/+Ay+USnKxhbo+Cj7i4jsLItswiVLn9iHKYbsiEyHDCraZJkoSvfjooOgZRky1Zsw8XXdAOVt6ihR1TvQvx+QNY+eMBziJSWNl3uBxHiqrRuU2C6ChEZCB+v4pPVu8VHYPojHz+4wFMv6ir6BhEpnfxxRdjxIgRePDBBzFq1ChIBu+BoUHDD9u4uI7Cy6ers3DDhF5wcvKGKKTCqaapqoYtGYUor/KJjkLUZIeLqrDvcBl6dWouOgqdIdO9A/liQ7boCERnbOmavZg9PRVRTtP9ShLRWSqp8GBvbpnoGERnpKzSi7S9R3FBj5aGvukmCndffvkl2rZtCwCorKyEJEmIjY0VnKphPn8AK9dn6764rjJvJ4ozv4YkSZBt0UjudyWszngU7lwCT1kOoAHOxHZo2WcaZIsNVQW7UJS+HJLFilapv4fT1Q4AkL/9Y8SlnI+YFt10zU/irdqcgxsm9hIdg8j0wqmmef0BLPmei+so/Hy8Kgv3/CEe0U6b6Ch0BhrtzZSfn3/Kr61bty6oYc5VVk4pisrcomMQnbEftx+BxE5pRCEXLjXN7VWwdO0+0TGIzspna/fB7VVExyAytbZt22Lt2rWYOHEiBg0ahEGDBmHixIlYs2aN6GgNWv7Dfl2vpwb8yN/2AVIG/hEdRt2F2OSeKEpfhpKsVdBUFR1G3YUOo++CFvCjZO9qAEDxnq/R7sLZSO53JUr2fg8AcJcegqp4OWkTodxeBd9tzoGisKMHUSiFU00rq/Rid3aJ7tetzNuJ7DXP4eDaucjZ8Cp81cW1tW77R8he8yyyv38W+ds/ghrwAwCqCnbhwOqnkb3m2drFCsfkb/8Y1UVZuucn8bZkFPDstjDU6FDxzJkzUVlZedLj8+fPx+233x6SUGejxuPH0jUc5KLw5FNUrNmSiwDb/BGFVLjUNFmS8P2WXNExiM7Ktqwi+PysZ0ShtHnzZjz66KO48847sWXLFmzYsAG33347Hn30UWzatEl0vHr2HCpFSYVH34tqKqABqr/2uqrigyRbEdW8M5p3GwNJkiFJMhzxbaC4a3e3SrIVquKF6vdAki3QNA1Hd69Ei14T9M1OhrJ83QEoKmsaUSiFS01zexV8+p3+kx5cjEDBoGnA5+v2w+vn5E04aXTiZtiwYbj11lvh89X2b6yursbtt9+Ojz76CG+99Vao8zWZpgGbdhWIjkF01lb8eAB+TtwQhVQ41DRV1bAxPY87FihsaVrtWTe8KSAKnfnz52Pu3Lm45JJLEBMTA5fLhfHjx+O5557D/PnzRcer4/b48c1G/Q9wlq0OJPebjpz1L2HfN4+jLHs9knpejpgW58Ee2wIA4K8pRemBHxDbui8AIKnnBORtfR/FWavQ/LxLUH7oZ0QndYUtKlH3/GQcOQWVKKv0io5BZGrhUtOsFglrRZzXxsUIFCRrtvK8wXDT6MTNgw8+iHbt2uH//u//kJWVhSuvvBJ+vx9LlixB//799cjYqOODXAFVEx2F6Kxl51Wg2u0XHYPI1MKhprl9Cr7jbhsKc2u25kLT+L6MKFSKi4uRmpp60uP9+/c/bVtQvVmtMjam65/HW5GH4sxv0WH03egy9mE063Yxjmx+p+51yVOWi5z18+HqOByxybVnmEQ374QOI/+G9sNvg8Uei4qcn5HYZTSKs1Yjd+MbKNq9Uvfvg4zh640HuRiBKITCpaZlHipDjUf/xXVcjEDBUlBSg/yj1aJj0Blo0qkaTz75JDRNw9SpUzFt2jQsWLAALpcr1NmazO1VsJazhmQC67YdQYBb8YlCyug1zWaRkZZVJDoG0TnJO1rNxQhEIeR2n/pcT1k2zsGJu7NLhAxyVRdlIqpZR9hjmgMAXB0vhK8yH6q/BhWHtyF342tI6jkezbtd3OCfP7rnKzTrejEUdxlqju5F2yE3IeCrRs1RngsQidb8kgtJdAgiEwuHmub2Kvh20yEh1+ZiBAqmL3/KhsfH7h7hokmvgLIsY+7cuRg0aFBdexkjsVllpO09KjoG0Tlbv+MIvDwsjCikjF7Tdh0oho+H4JIJcDECUegkJycjLS3tpMfT0tLQsmVLAYlOVuPx45uNYga5nAltUFO8H4q39ly7qvx02KKbwV16EEXpy9B2yEzEt2l4p6234ggUdxliW/WGpiqQjg0aSpJUd+gzRZbCUjcKS089sExE5yYcaprVIuFnATtIAS5GoOBan5YHWeJyhHBhbewJs2bNqvs4EAhg3rx52Lp1K2w2GwDglVdeCV26JkrfXww/B7nIBDIOlkLiCyhRyBi9prm9Cr7/hW3SyBzW7ziCsUPaI9ppjJWSRGYye/Zs3HPPPXj44YcxcOBAKIqCjRs34oknnsDTTz8tOh6A2sV1P+8SM8gVndQVzbqMRu6GVwHJAos9CimDbsCRzW8DAArSFtc915nYEcl9p9V9XrRrBVr2qf3cEd8aFnssDqx+Gva4ZMS06K7vN0KG8d3mQ7h6bHfYbRbRUYhMJxxqWnZeBSqqxSz6cya0QVn2eijeSlgdcQ0uRnC62jX4Z09cjOCtyONiBEJJhQf5xdVo3ypedBRqAklrpAH5kiVLTvsXTJs27bRfDzW3V8Ern6Zh9eYcoTmIguX+Pw7E8NQ2omMQmZLRa5pfCeBP//pa2E0BUTDJsoQP51yOKEej64SI6CysWrUK//73v5GdnQ1JktCpUyfcd999GD16tOhoAIDtWUV46JX1omMQBUXblrGYe9doOO2saUShYOSa5vEqePPzdKz8MVtYhrLs9SjLXl+3GKFln6k4svltqH43rM5fB+B/uxgh96cFaNlnWt1ZOHlbP4Sn9CDscclIueB6SDInoyPRFb/rimvH9YCDixEMr9GJm9P58ccfMXz48GDmOWM+fwB/fpyDXGQeF/Zrjb9d3R/RTpvoKEQRxQg17cCRctzx7PdCMxAFExcjEIVeWVkZABjqvDa3149Xl+zEKkHnARCFwsJHxqFZglN0DCJTM2JN8/kDmPn/vkFppVd0FKKgaNsyFnPvHA0nF9gZXqP/Qunp6Xj88cfhcrnwxBNPoFmzZjhy5AieeOIJrF27tsE+lHo6XFTFSRsyla17imCzsq0MUSgYuaZ5/QGsYZs0Mpm12w7j/O4tEcPFCERB9fXXX5/265deeqlOSRpmkWVszyoUmoEo2LZnFeF3AxtuR0REZ8/oNa2wtIaTNmQquYVVCKhnvY+DdNToxM2jjz6K8ePH48iRI5g/fz6GDBmC+++/H6mpqVi2bJkeGU/J6w/wLAAyHbdXwb7ccvTo2Ex0FCLTMXJN0zQNP+0UcxYAUahs3VMEOxcjEAXdHXfcgaSkJHTu3Bm/baAgSZLwQa4qtx9HyzxCMxAF25Y9hRjSpxU7IxAFmZFrWkBVsXl3gbDrE4XK7gPFGNirlegY1IhGJ24qKytx4403IhAIYNy4cfjiiy/w2GOPYcKECXrkOy1V1bB5F19AyXzWbM1Fp5R4ONhDmSiojFzTPF4Fh4uqRMcgCiq3V8H+wxXo3iFRdBQiU3niiSewbNky1NTUYOrUqZg0aRLi441xyKymafglg7ttyHx27jsKq4WLEYiCzcg1zeMNYFtmkegYREG3aXcB+nRN4tltBtfov05UVBQAwGKxwOv1YsGCBejVq1fIgzWFRZaQU1gpOgZR0GVkl3LbIlEIGLmmZR4qEx2BKCS2ZxWia7sEWGQOdhEFy/Tp0zF9+nQcOXIEy5Ytw4wZM9C5c2dMnz4dI0eOhCzw983tVfDLHk7ckPkUl3tQ4/HDzsOciYLKyDXNYbNg14ESYdcnCpUd+4px9qfek14affU7cZtiYmKiYQa4gNqefPwhIzPKzqvgDQFRCBi1pvmUAHbsOyo6BlFIZB4qg8cbEB2DyJRSUlIwe/ZsLF++HH/605/w+uuvY/To0UIzWS0ydh0oFpqBKFTS9vL9GlGoGLGmFZW54fYqQjMQhUJOQeVJrQnJeBrdcaOqKsrLy+v+MU/8GABcLlfo0p02l4b0/XzTROakBFQUlbrROilGdBQiUzFqTfP7VezN4Y4bMqe9uWWw8pwbopA5evQoVqxYgWXLlsHj8WDGjBlC83h8CorLeb4NmdOWjEIM7JnMc26IQsRoNY2L68jMMrJLMaBHS9Ex6DQanbjJzMzE0KFD6wa2hgwZUvc1SZKwe/fu0KU7DY9PwZ6DpUKuTaSHPQdLOHFDFGRGrWkOuwX7DpcLuTZRqBWXexAIqAB3khIFjdvtxtdff43PPvsMe/bswbhx4/DYY4+hX79+oqMhI5v3aGRe6fuLYZEl0TGITMWoNa3G48dOTtyQiW3eXYDeXZrDwfs0w2p04iYjI6PRvyQ7OxsdO3YMRp4mkyQJWVydTCaWfqAEQ/u25kFhREFk1JpWXuXlFnwytey8CvTq1Fx0DCLTuPDCC5GYmIjJkyfjr3/9K2y22tX/6enpAIDevXsLyaUEVGQc5FkAZF4FJTWQJE7cEAWTUWuaJEnI4IJxMrEDR8qhKConbgwsKCPCd911F5YsWRKMv6rJLLKEvOJqXa9JpKd9uWUIBNhvkkhvImoa26SR2e3cV4zuHZpxlTJRkCQmJgIAPvvsMyxfvrxe209JkrBq1Sohuby+AA7lVwq5NpFeCkpq0C45TnQMItMwak2zWWUUcNyRTCynsBI2trQ2tKBM3Ig4zKj2ECXdL0ukm+y8CjjsnPUm0pveNc3nD7B3MpleVk4ZPF4FMVE8E4AoGFavXt3oc1asWIGJEyfqkOZXsizhUAEnbsjcDhwp58QNURAZtaaVVnigctyRTKy8yocAf8gNLSjTanpvFVZVDen7i3W9JpHe/IqKojK36BhEEUfvmuZXVLb+JNPbl1sGq4WruYj09MYbb+h+TZtVRkFJje7XJdLT3txy+JWA6BhEEUVETcstrNL9mkR6y+euMkMLyztoj0/hIBdFhKxD7KdKZHYOuwUHjlSIjkEUUkVlbqjcKk2kKxFdEYrLPVC5cpNMLqegEj6/KjoGUUTRu6apqob9h8t1vSaRCPw5N7awnLhRNQ1HuROBIkBOYSVvfolMTlU1uL2K6BhEIVda4REdgSiiiDhA/VA+FyKQ+eUUVPLMNiKd6V3TvP4AW39SRNiXWw6fn7tIjSosJzFu8bEAACAASURBVG5kSUIxb/4pApSUe/kCSmRyldU+0RGIdFHC925EphZQ2fqTIkNhaQ0sbP9JZGqqquEwW6VRBMgprIRf4S5Sozqndxs+X+1gU8eOHYORpcnsNgtXbVJEKK3w8KAwIp2IqmmllV5dr0ckCs9tIzI3n09ln3SKCJoGlFXx/RuRmTlsFhwu4sQNmV9+cTVk7iI1rEYnbnw+Hz766CN89dVX9R5fvXo1JkyYAACYO3duaNKdgqpq8Pi4C4HMr6SSE5REwWTEmlZUxkOcKTIUFFfznBsiHel+HoCmobyKu0gpMnDHNJG+RNS0Krdf12sSiVBe5YOVu0gNy9rYEx555BFkZWWhqqoKFRUVGDduHO677z6sX78eM2fO1CPjSSr4JokiREm5hy+gREFkxJqWX8yJG4oMxeUe+PwBOO2Nvv0kojNQWVkJSZIQGxtb7/FJkybpnqW8mrsQKDJwxw1RaBilpvEMUooUbq8CbrgxrkbvnDdv3oyVK1eitLQUd955J958802kpKRgxYoVaNeunR4ZT8K2MhQpyqu8sFk5cUMULEaraT5/gO2jKGKUVHoRCHDHDVGwrF27Fs888wz27t0LSZLQpUsX3HPPPRg9ejQA4KabbtI1j8UioYI7bihCsHU7UXAZraZVe7jbhiKH26sgNtouOgY1oNER4ZiYGNjtdiQnJyM7OxsTJ07E66+/LmzSBgCOsq0MRQhV40oPomAyWk3zB1SUlPPGnyIDB7mIgmfz5s149NFHceedd2LLli3YsGEDbr/9djz66KPYtGmTkEw2q4xy7kKgCHG0zK176yYiszJiTauq4cQNRQ62BTSuRnfcSNKv+6VcLhduu+22kAZqCraVoUhSUe1DTJRNdAwiUzBaTdM0oISD2RQhSio8sFq4D58oGObPn4+5c+ciNTW17rHx48ejVatWePHFFzFo0CDdM6mqBp+i6n5dIhHKq3zwKyrsNovoKERhz4g1rbKGO0gpclTW+NCqeYzoGNSARnfcnDjI5XQ66z7euHEj+vfvjylTpmDy5MkYP348Fi5cCAC4/vrrsXHjxnp/z/33349PP/0UANC9e/d6X3vsscfwhz/8AdXV1Y0G9isBFJeHvq2MpmnI37YIJfvWHPtcRWH6Zzjw3b9xYPXTKDu4oe65vqoi5Kyfj+zv/4ODP7wIX1Vh7Z9RFeRufAMHVj+NgrRPfn1+dTFyf1oQ8u+BzIErlImCp6GaJqqeAYBFllBaGdrfcdYzMoqySi9sVg5wEQVDcXFxvQGu4/r374/8/HwBiYAaD3eJU+Qor/ZCCXCikigYjFjTeI4VRRIeSWJcje64ycnJwaxZs076uLS0FHa7HcuWLQMAVFVVYcKECRg+fPgZBZgzZw7279+P1157DVFRUY0+X1U1eP2hfYPkrSxA4c6l8JQdQvO4VgCA8oM/wVdVhI6j/w+q4sWhH1+CI74NohLbI2/rh0jsPALxbfqjujADR7a8gw6j/g/VhXtgi3Kh7ZCbkLvxdXgr8uGIb4WiXcvRotfEkH4PdGpVBbtxNOMLaKoCR3xrJPe7CgFfNfK2vA1V8aFZ14uR0L52RUdF7hb4qo8iqfs4YXmrz+AmODc3F5dddhm6dOkCAFBVFdXV1Zg6dSqGDBmCefPm4Z133gFQ+zt74403YsCAAbj//vtDkp3IaBqqacfrWevWrfHKK6/oVs8AQJIAXwhrGuuZ+YVTTQuoGlRNg4ym7bphTSM6Nbf71AvZZFnM+YjVbLNBEaSi2geVrdKIgsKINa20ggPZFDlK2b7dsBqduHnwwQfrPh437tcb/X379qG8vLzuc6/XC4vFgri4uCZf/KmnnsL+/fvx6quv1tvNczqqBgRCvLKlLHsDEtoPhi3KVfdYVX46EtoPgSRbYLFHIy4lFZWHt8LqTIC/uhBxKbWrA2Ja9kDBjiXwVhyGJFuhBnzQVAVawA9JtqCqYBesThcc8Skh/R6oYYq3CgXbP0K7C2+DPbYFinavxNGMLyDJViR2uQixrfri4Jr/IKH9IKiKB2XZG9B22C1CMwfUM/t5b9myZd2EKgAUFBRg3LhxSEpKqnusuroaM2fOxODBg3H33XcHLSuR0TVU047Xs+Of61XPgNodQKFcrcl6Zm7hWNNUVQPOYNMNaxpRw5KTk5GWloZ+/frVezwtLQ0tW7YUkimgchCbIofPH4DUxIUIRHR6RqtpiqKiopqt0ihyePwB0RHoFBqduJk2bVrdx5WVlZAkCbGxsdi4cSPee+89TJkyBaqq4tChQxg/fnzdi+pDDz2E6Ojouj+bl5eHwYMH133+73//G2+++SYWLlx4RoNcAKAEQntTkNx3KgCgpiiz7jG/uwzWqIS6z21RCaiuzIfiKYPFEQ9J+nUVgNWZAMVdjpjknqjMS8PBtc8jtnU/WKMSkb9tEdoMvjGk+enUaooy4XS1gz22BQDA1WEoDq59HgkdhkFVfNACPuDYG/DizG+Q2HkUZItdYGKc86BuUVERNE1DTExtv8qamhrccsstGDp0KO68885gRCQKGw3VtJSUFLz33nt466238L///U/XeiZLoV2MwHpmbuFY09RzHNhlTSOqNXv2bNxzzz14+OGHMXDgQCiKgo0bN+KJJ57A008/LToekempmgZOVRIFh9FqmgbtnN+zEoWTUG+QoLPX6MQNAKxduxbPPPMM9u3bBwDo0qULJk+ejD59+tRrUTFz5kwsWFDb637OnDkYMmRI3d/x27YVe/fuxdNPP40HHngAy5Yta/LKZk3ToJ7hDoTg0IATVtRoGmp73GhavTMT6p4ryZAkGa1Sr6p7tDjzW8S3G4SArxr52z8GtACadx8HZ0IbXb4DAhRPOazOXwcsrc4EqIoHrg5DUZD2Mcqy16NFrwnwVhbAW1mAFr0mCUxb60wnKgsLCzFlyhR4vV6Ulpaib9++mDdvHux2O9xuN2699VZkZmbipZdeClFiImP7bU1r3bo12rZtW6/1px71DDi240b3mwLWM7MIx5p2pm1lWNOIGjZs2DDce++9mDNnDg4ePAgA6NSpEx555BEMHDhQcDoi81NVcL8NUZAYraZJkCDL/A2nyMFd08bV6MTN5s2b8eijj+KBBx7AsGHD4Pf7sWHDBvzrX/+qt2UxNjYW48ePx/r165t04RdffBF2ux0//PAD/vnPf+K5555rcuiAgF6ytigXFE/Frxm8FbA6E2A99rh2woCX4qmA7YTVzADgd5ei5mgW2g67FflbP0Ri51GwRScif+v7aHfhbbp+L2dr+bNTREc4Z6+8koe8vDw89ljt96IoCnqv/Ac+ffb3iI7+U93zZs6ciZffmovc3Fy8//77iI2NxSOPPAKXy3WKv9k4jreVUVUVTz31FPbt24fhw4dj06ZN2LFjB/72t7+hc+fOeOihhzBv3jzRcYl01VBNe/vtt/Haa69h06ZNGDRokK71TAKg6fwmifWsFmsaaxpROPP5fBgzZgzGjBmDsrIyAAiL32kKvmduG4oencW0x4t0iscNwCY6BlHYM1pNk6Tazgikv8VzxsLubNp5sUSRoNGJm/nz52Pu3LlITU2te2z8+PEoLi7GCy+8UPdYIBDAzz//jF69emHz5s2NXthur23V8c9//hOTJ0/GJ598giuuuKJJoS0nrQgOvZjk3qjI2YTY5J5QAz5UHtmOln2nwRblgi2mOSqPbEd8m/NRXbgHkiTBfuwQ6OOKdq1AUs/LIUkyNFWBJMuQJAlqIHwO8Zx2zzLIsnzsP0AGIFtkyFLtqnFJkmCRT/jYIh1bqQDI8rGPpfqfS/Kxf09Jgiwde1z69XmSJEHGrx9Lx54jSxIgAbJ04vVP/POAfOwxHPv7JBnIylexZ8c+vL1yFyRIqCgrhDM6Fst+OHTsz8tI37oOqq0ZtudoeO6f/8IdD/0Xu7ZtwAOPz8X4aTdAxq/Xk47lBI5d//jj+PXr9f732Pdc+0ca+Nrxz0+4RvtWcUiMO7P2S0Dt93Lvvfdi6tSpeOONN9CvXz/0798ft912G9xuN6ZOnYoPP/wQ11xzTRB/SoiMraGaNmTIEKxevRrz58/HoEGDdK1nGqD7ai7Ws1pX3Lf82Ou3DIv8a/2wHPtfSULdx/Kx+iDLx1/nT65nx7+Gur8Dx55z7O869uIv49drHa8h8vE6Va+2nFzLLPLx2lf7tX2FKjJ27sd7X+6GJEmoKC1EVHQsVqzPrftzO39ZB83eHOmHgX8/8i/c9c952PnLejz0+POYcMUNx/5eAJDq1dPj+SQAkny8Lp1Q5+pq1wnPrVfLGqhvALp3bAar5cwPmWVNI6rv6quvxpIlSwAYZ8JG40HtQuw+VIEuCX7kLrjr2DZa0oMjpStaXfuw6BhEpmC0mnb8vTjpr6TCi6htX6Nk9buio0SUxIuuReLwpo1hkL4anbgpLi6uN8B1XLdu3VBZWYkpU6bUtnpRFHTv3h0333xzkwa6jouPj8eTTz6J22+/HQMGDECnTp0a+RNiXkBdHYbCX1OMg2ufh6YqSOgwFNHNuwAAWve/DgVpn6Bk7ypIshWtL/hDvTMCqouyIFsciErsAABI7DwK+ds+AqAZom1JUykqaveEI3x7HyreBBzM2o33lq0/dpDzF7A364H3v94DAFADPuSsfx9th96Mt1bsQnmlG2+vzEBV/mF4yw8jBzt0z3zfHwdiROrZtR+yWq2499578be//Q1z5syBzVa7IiwqKgrPPPMM/vznP2PgwIHo2rVrMCMTGdapatrBgwexb98+TJ06Vcd6VjvIZdG5prGe1fIpx2tZmNe0zF14e8mPdTXN1qwH3vliN4DjNe09tB16M17/LB1llW78b/kuVOXnwluei4NI0z3zx09OOKuJG4A1jehEnCSh4xau3IXJw8bC2b4XPAd3io4TOQQsJiUyK6PVtOOLlUh/LyxOxxM3X4ay9UugeqpEx4kcskV0AjqFRidu3G53g48PGTIEXbt2rTsT4ETHz7050VNPPVX38Z49e+p9bdiwYfjll18aDQugbleEHlqdf/Wv15UtaNl7coPPs8e2QLsLZ53y74lp0Q0xLbrVfR7VrCM6/e6e4AWlJrM6YpGcehWObHkX0AKwRTdDq/N/XZ1bkrUaro7DYLHV7nBJ7DwKB9c8C9kWhZQLrheS2WY9t5/3UaNGoX///njhhReQnJxc93hqair+9Kc/4a677sLixYvhcDjONSqR4TVU04YMGYKtW7di4sSJWLp0ab2vhbKeAbULY/VYjMB6Zk7hWNPO9eedNY2oltfrxa5du0452NW7d2+dE5Eoqgqs3l6EkRddh7yFD4iOEzkkfcYkiCKB0Woad9yIk76/GIVlbiQMnYzS798XHSdiSJy4MaxGJ26Sk5ORlpaGfv361Xs8LS2t3hk3ejneuoTobMUm90Rscs8Gv5bU47J6n7s6XghXxwv1iHVKNkvTX0Dbtm2L1atXn/T4//73vwaff8cdd+COO+4462xE4cZoNU0DYNFpMQKZU7jVtDNpd8uaRnRqOTk5+Otf/9rgIJckSVi1apXumc52Nx2du9eWpmHMY2Nhb90Fvrx9ouNEBNnBMxiIgsWINY3jjuI8/3E6nrh5Asp/WgbVUy06TkSwRMWKjkCn0OjEzezZs3HPPffg4YcfxsCBA6EoCjZu3IgnnngCTz/9tB4Z67HIMmKieAAgRQ6bjTfBRMFitJoWCKiIibKhrMqr+7WJ9CZJteflENG569q160m7REWLcjZ6a0kh4vGp2JhRjNTR16Lgwzmi40QEizMWElspEQWFEWua3cYdCKKk7y9GUZkHCUOncNeNTizRCaIj0Ck0+u562LBhuPfeezFnzhwcPHgQANCpUyc88sgjGDhwYMgD/pbNKqNlIle3UORwxbLdC1GwGK2mqZqGxDgHDhexfy+ZX3yMHYqi8kaYyKSi7Jy4EemlxWl45+GLYWveBv7iw6LjmJ4cFQvI/JknMqtm8U7RESLafz9Jx+M3TUD5hqVQvTWi45ieHB0nOgKdQpPeaYwZMwZjxoxBWVkZAMDlctX7+ooVKzBx4sTgpzuFFonRul2LSDRXHCduiILJSDVNliQk8qaAIkTzhCj4OXFDFBRNWWyQnZ2Njh07hj7MMXabBZJUe34b6a+i2of07DJ0HHk1ipY+JzqO6clRcZCs7ARCFAxGrGmJ8RyHESlt71EUlXtqz7pZ86HoOKZncbJVmlGdUQ8ml8t10gAXALzxxhtBC9QUSQkc5KLIIEtAtJM3BEShYISaZrXKSOTkLEUIrlwkCp6HHnqo0efcddddOiT5lRJQEcP3rUI9v2g7Ys4bCEt8kugopmeNdbFVGlGQGLGmJcTwHk20Fz9JR8LgSZAdXLwfavz/2LiCcnhGQweIhRJbR1GkiI91QAmoomMQRRQ9a5rdakGSi+0/KTI0T3DCYuEgF5Fe9L5HUwIqd5EKVljqxoEjlXBdOF10FNOzxCaKjkAUUfSuafGxdl2vRyfbnnUUR8s9SBgySXQU05PsfP9mVEGZuNF7pUlsDF9AKTI0T3BCUThxQ6QnvWtay2Zc3UKRoXlCFNukEelI73qmauAuUgP47+KdiOt3EeToeNFRTI0HORPpS++aFhfNcUcj+O+nu5AwZBIk7ggJGclig2ThmW1GFZSJG71ZZQl2a1hGJzojbCtDZH4tuOOGIkTrpBjIbCtDZFqyBO64MYD9R8qRX1zDFcohZnW1FB2BiEJI0zTERrH9p2jbM4tQXOFFwmD9zlWPNFZXS2h+n+gYdAphOfvhU7gNnyJD84QotpUhMjm2/6RI0TKRk5REZuawW5HSIkZ0DALw0pJdSBh4OSQ7X3dDQrbAwh1NRKbmV1Q05/nahjDv091wDZnMmhYitmatoWns9GNUYXnGjapqSIznQBeZXwuXE3Yr28oQ6UnvmhbH9p8UIbiLlMjcLLKEbm1domMQgLS9R1Fa6UX8BeNERzEla3wSNIWrk4nMTNOAlBaxomMQgF/2FKK4krtuQsWW2AqSlWMSRtXoxE1lZeUpv5aRkQEAmDRJ323Ysgy0bs4XUDK/1s1jIMvccUMULEasaVaLjBhuw6cIkMDdZURB43a7G31Ox44dQx/kN9q3itP9mtSw1z/PhGvYNEgWvscINluz1tBUrk4mChYj1jSnw4KOKdxZZxQvLdkN19Ap3HUTArYW7SFb+V7BqBqduJk9ezZ8vpNXk3z22We49tprAQA33XRT8JOdhtNuRfcOXM1F5tepDQ+9JAomI9Y0nz+Azin8XSdzc8U5YOFCBKKgueKKK5CVlXXa58ydO1enNL9qnhAF/qobw7rtR1Dj0xDb73eio5iOrVlrHuRMFERGrGkWWUaPDs10vSad2paMQpRW+ZAweILoKKZjb9FOdAQ6jUYnbpo1a4a777677vNAIIA5c+bg8ccfx5NPPhnScKciSRJ6dmwu5NpEerFaJLRqzj7hRMFkxJpmt8no2o4TN2Ru3dq64Fe4OpkoWGbMmIHrr78eH3/8sego9fgVFcnN+P7VKN79dj8SR/0ekMLyaFvDsie1g2zjLlKiYDFqTevAXaSGMm/JLriGToVkZ/vlYLK5WoqOQKfR6Du4Z599FtXV1Xj88cdRXFyMG264AVu2bMHixYtx2WWX6ZGxQW1bxkLiai4ysQ6t4uHzB0THIDIVI9Y0m9WC3p24GIHM7bwOiXA6eGYbUbDMmDEDH374IRYvXoy///3vTWozowdV1dA2mS2tjWLl+mwokg0xPS8UHcVUHCldRUcgMhWj1rSEWAfsVk58G8Xm3bW7buIHcddNsMiOaMhOLrgxskZfgWw2G+bNm4f09HSMGzcOnTt3xqJFi9ChQwc98p1SQNXQmrsRyMS6tXNB5uwkUVAZtaZ1bcf2n2RufbskwSLzxpcomDp27IgPPvgANpsNY8eOxaRJk+r+E8Vhs/CcG4P5dF0uEkdfKzqGeUgybGwrQxR0RqxpPn8A7ZJZ04zkpaW74Ro2FZKNu26CwdG6K1T/ya3kyTia1Jg1KioKCxYswPXXX4++ffvCbreHOlejNE1Dl7YuHDlaLToKUUj07twcTgd7JxMFmxFrWkKsA1EOK9xeRXQUopDg4a5Ewef3+/H8889jzZo1uPvuu9GunfjBZKtVRq+OzfEJ9oqOQsd88PUeXDlqLKK6DoB77y+i44Q9W1IbIBBo4kgKETWVEWsaJKB9q3jsO1wuOgkds2lXAcqr/YgfdDnK138qOk7Yc7TpxtafBtfo2405c+bUfdyhQwc89thj2LFjR91A10MPPRS6dKfhtFtxXvtE/LDtsJDrE4Vadx6ERxR0Rq1pXl8AnVLisetAiZDrE4VSkssJK3fbEAVVRkYG7rnnHrhcLixZsgStWrUSHalOr058D2s0X23Jx6Wjr8NhTtycM2fKeWDPdqLgMmpNc9qs6N7ehe+25IiOQid4eWkG/jFjGio2rYTm94iOE9acHftCsnAlgpE1+q/jcrnqfXzeeeeFNFBTybKE3rwpIJOyW2W0SIwSHYPIdIxa06xWGV3auDhxQ6bUtW0ilIAKB3jGDVGwXHPNNbj11lsxa9YsSAYbRLZaZbRuHoO8YnZGMIr/LU/H+H9dAkfbHvDmZoiOE9acHXpD5sHYREFl1JomyxIG9EgGsEN0FDrBxvR8lFf3QPzAy1C+YanoOGHN0aqz6AjUiEYnbv7yl7/okeOstGP/ZDKpjikJ8PoCsEZxhTJRMBm1pjlsFvTu0hzL1+0XHYUo6Hp0SEQUW38SBdXChQuRmpoqOkaDNA3o3aU5J24MRFFUrNtZhCEXXYe8dx8RHSesOdv1FB2ByHSMXNOSXFGIi7ahssYvOgqdYP6yDNx/3RWo2PwFNL9XdJywZIlrxt02YaDRf6FZs2ad9uuvvPJK0MKcKU0D2ifH4VBBpbAMRKHQrZ0LVotxVpoQmYWRa1rvTs2FXZsolPp0aQ5ZZk0jCqbU1FTk5eXhgw8+QGZmJpxOJ8477zxcffXVaN5cbD2JclgxsEcyvv35kNAcVN/8T3dg5D8vgb1lB/gKD4qOE5YkexSscez6QRRsRq5pPn8AfbsmYX1antAcVN9PO/NRUd0T8ReMR/lP3HVzNpztewFqQHQMakSjy/nHjRtX99+ePXvqfT5u3Dg9Mp6SRZYwpI8xel8SBdPwfilw2DnzTRRsRq5pTocF7ZO5k5TMxWGzoFNKgugYRKaTnp6O6dOno6ysDCNHjsTgwYORk5ODyZMnIyNDfCusPl24GMFoajwKtu0tQeLoa0RHCVtRnfpBU3yiYxCZjpFrWrSzdjECGc/8ZbvhGn4FJJtDdJSwFNNjGGRHtOgY1IhGR4anTZtW9/HChQvrfS6a3WbBqP5t8fGqLNFRiILGYbege8dE0TGITMnINU2WahcjcBcpmcn557WAElBht/F8G6JgmjdvHp577jkMGzas3uNr1qzB888/L3QHKQA47Va0SIxCUalbaA6q74WPtuOtBy+GNbEVlNJ80XHCTmyPYZDsPIeUKNiMXNMkScKAHi2FXZ9ObcPOfFS6eyL+gstQ/tOykF9P0zQ8++NhdEx04sreSQioGl7+OQ87Cmpbww5qE4uZF7SCJElYmVmCj3cWIc5hwQOj2qNVnB0A8PCqbNx8QSu0d4k+K01CdCdjtiek+s7oAA0jHRJ2XEpSDOJj7KJjEAVN//NawK+oomMQmZ7RaprdZsGo89uIjkEUVKP7t+H5NkQhcPjw4ZMGuABg9OjRKCwsFJCoPlVV0a9rkugY9BullV7sySlH4oirdLmepmn4z7pcLE4/CgAIqBpe/OkIblmWhVuWZeG1zXnQNA0AsDKzBH/+dA/u+Hwv8it/3dXy8KpsHCrz6JK3MVFdBxju/SORGRi9psVF29E8QfRAOzXklc8yanfdWEM7LnyozIN/fJONdYfK6x5bvb8Mhyu8mD+pK16e1BU7Cmqw7mAFAOCjnUV4dUo3TO+VhOV7igEAP2SXo32CwwCTNoCjdWfREaiJwv7kcyWg4gJuWyQTGXV+W0RzkIsoIrVpGcvFCGQasgQM7NWKg1xEISDLp76NOz4QLlKU04bfXdBOdAxqwAsfpSGm54WwxIZ2h7/ZBrnsyZ0gSWE/fEJkSEavaUpARb+uLUTHoAb8mJaHSncA8RdcFtLrrNhTgnFdEzGyw68toFVNg0dR4Vc1+AMqFFWD7dhZ1VZJgldRUeNXYZMleBQVn+w6ihmpxti9FdX1AkgWjjuGg0bfeZSVldX9FwgEUF5eXu8x0aKdNozuzxXKZA61g1zJHOQiChGj1zRF4WIEMo8eHZsZ4mabyIzC4b1iz47NuOPOgA4XVSGnoBIJw0LbLtZsg1zR3TjIRRQqRq9p0U4bLh7IxQhG9eryPXCNCO2um9uGpOB3nV31HrukSyJi7RZcvzgDMz7eg5Q4O4a2iwcA/GlAMu796gB+PFiBKT2T8OGOIkzq3gzRBmkfHdtzGCSrTXQMaoJG33kMHTq03udDhgyBJEnQNA2SJGH37t0hC9dUfbomwWqRoAQ4OEDhjYNcRKFl9JoWdWwxwndbcoTmIAqGEakpcNiNcXNCZDY5OTmYNWtWg1/Lzc3VOU3DlICKwb1bYc0vxshDv3rxk3Q8c9slKPthEVRPdUiucduQFADAL3lVdY9d0iURPxyswPWLMxBQgQEpsScNcjWLsuHuEW0NOMg1nINcRCESDjWtV6dmiHFaUe1RREeh31i3/QhmTe6OuAGXouLnFbpd9720QiQ4LXj/qh7wBTT867tD+CT9KK7onYQRHRIw4tjChSOVXmQU1eCP57fEK5vycLjCi/6tYzG9l5iWsnJ0PGyJrYVcm85coxM3GRkZ9T7Pzc1FWloaevfujQ4dOoQs2JkIBFT06ZKEbZlFoqMQnZMRqW3gsHMlF1GohENNEO163wAAIABJREFU42IEMovhqW1gOU3rCyI6ew8++OApvzZu3Dgdk5xatNOGsYPbc+LGgPYcKkVRaQ3iB01E2Q+LdLtuuA5yWeNbwNqslZBrE0WCcKhpAVXDsH4p+PbnQ6KjUANeXZ6Jv195FSp/+Rqa4mv8DwTB+kMVmD24NWwWGTYLcEkXF9YdrMAVvevXqtc25WPmBa2wNa8Kbn8A/7q4Ax78NhtD28YhJd6hS9YTxfYeCU1VYex9bnRcoyPEW7duxf3334+WLVvilltuwR133IEOHTrgyJEjePzxxw3xIuq0W3BhvxRO3FDYG56aAovMl0+iUAmHmqZwMQKZQLvkOEQ7uRCBKFSmTWu4zVV+fj7eeecdndOc2vF2aW4vVygbzSufZeCh6yeh/Kel0PxeXa4ZtoNc/S4CuJ6GKGTCoaZFOay4bGgHTtwY1A/bDuPWSechrv9YVGz6XJdrdm0WhbXZFUhtFQtF1fBTbiV6tIiq95yNuRVoHm1D1+ZR+CmnAhZJqmsN6BW0UDN+wKWQ7frXUjo7jS6DfOqpp3DnnXdi/PjxuO222/Dyyy9j6dKlWLRoEV5++WU9MjZKlmWMOr8NB7wprLXnIBdRyIVDTYuyWzB2cHvRMYjOyYV9W0M2eL9yIjPZvn077rrrLlxyySXYvn276Dh1lICKwb14dpsRbd5diMoaP+L6j9XtmscHuQA0aZDLH9AMMsg1FrItdGcnEFF9Rq1pnVIS4IrjgLdRvbYiE4kjfw/Jok9by1sGtkK1L4Cbl2bi9uV7kRRtxZUnLETwBVR8kFaEG/rXntU2ICUWhdV+3LgkE61i7eiU6NQl54lszVJgTWih+3Xp7DU6SlxTU4Px48cDAF5//XUMGzYMANCpUydDHSAmScCgXsn4aWe+6ChEZ2X8hR1htbClDFEohUNNk2UZQ/u05gplCluSBFw+vBPsBjmXgMisVFXFl19+iYULF2Lnzp2w2+14/fXXTzrPTaRopw1jh3TAmq2HRUehBrz55V7cMeVKVGz+ElBD/57jloGt8PLPebh5aSZkScL5rWMaHOR6fExt+9oBKbFYsacENy7JxPmtYoQMcjlSukF2ROt+XaJIEw41TVU1jEhNwYp1B0RHoQas2XoYt0w8D3EDxqJi08qQXOPvw9vWfRzvtOL+Ue1O+Vy7Rcbzl3ep9/mcSzqGJFdTxab+DpLEccdw0ui/lsXy6013fHx8va8ZZZALqL0pmDyqS+NPJDIgm1XGmEHtOXFDFGLhUtMCqobRA9qIjkF0Vvp2TUIUz2sjCqnXX38dY8aMwfz583HppZfiu+++Q2JioqEGuI7r2bEZErlC2ZBWb86BJwDE9hkZsmv8fXjbusmZ44Ncr009D69O6YbZg1NgO+H+5/ggV5zDWvf5nEs64n/TzsMdw8S8L4rrPxaSlbttiEIpXGqa02HFZUM7io5Bp7Hgc3133YSb+NQxkKz8/yacNDpKfOJAlpEGtRrSvX0imifovwqH6Fxd2C8FmsbGyUShFi41LcphxRQuRqAwNWVUFzgd3G1DFEr/+c9/MGjQILzwwgu46aab0LJlS8PWNQ3AOA50GdaH3x9E4uhrAK7APZnFithewyHJrGlEoRRONa1V82i0T44THYNOYc0vh1Ht0xDX/xLRUQzH2a4XFyKEoUbfne3ZswcDBgzAgAED6n3cv39/ZGZm6pHxjIwf1lF0BKIzNm10F0Q7OetNFGrhVNOSXFHo0iZBdAyiM5IQa8f53VoY9mabyCyWLVuG6OhoXHXVVbjyyivx3nvvQVVV0bEa5LBZMGlkZ/A4UmNa+v0+qNYoxJw3WHQUw4ntMQzg4jqikAunmma1yJg6mgvsjOyNlXuROOpqwMIOACdyDZ8Oyc4d0OFG0hpZ5n/48On7EbdpY6xWLtVuP/7wzy+hBIz5Ik/0Wx1bx+M/d4yEg21liEIunGpaQFWxfnsennl3s+goRE127aXdccXvurKmEemkuroaS5cuxaJFi5CVlYWpU6di5syZ6NLFWINKNR4/5n7wC88jNagbLu+FyanRyH31DtFRDKXt7Bdhb5YiOgZRxAiXmub1KfjjY1+hxsPzSI3q/UcuhnfDh6jY8qXoKIZgTWiJtre+ANnGHTfhptEdN23atDntf0YjScCIVL65ovBx1ZhuPNuGSCfhVNMssowhfVohIZZvrig8WC0yJo/qzEkbIh3FxMRgxowZ+Oyzz/DOO+/A5/Nh+vTpomOdJNppw9Vju4uOQafwzpe7IMUmIqpTP9FRDMPZoQ+ssYmiYxBFlHCpaZoGXDq0g+gYdBpvrMxC4qhruOvmmIShUyBx63NYMt1ocbTTht9fcp7oGERN4op1YEif1rBw4oaIGqBpwOUXdhIdg6hJRp6fAgtvCIiEGThwIJ599lmsXr1adJQGtW0Zi85sAWpIqgqs3laIxNHXiY5iGIkjfw/JxvNziUQxck1zOqy46uJufN9rYKs256DGD8Sdz7NuJEc04lJ/B8nC4xnCkSlHi1u4otCrUzPRMYgaNXEEB2SJ6NQcdgsmj+wMm9WU5ZpM5pqx3RHl4A0BkR5uvPHGuo9fffXVel+bOXOm3nGaxGaVcTUX2BnWgiU7YEtqB0dKN9FRhLM1bwNHSlee10akk7CsaRYLRpxvrI4NVN//vtyLZjzrBvHnX8Lz2sKYKUeCHHYLbp7SV3QMotOKclgxaWRnOGwW0VGIyMCsFhmTOMlLBjege0skxnNlMpFeSkpK6j7+8sv6/dsbOcJUGIss44KeyWjTIlZ0FGqAT1HxU0YxEkdfIzqKcK7hV0CSI3ugj0hP4VjTopxWzBjHFqBG9u3Ph+BWJMSlXiw6ijiyFa5hUyHbeZ8Wrkw5cSNJEtq0jMWA7i1FRyE6pasvOQ8W2ZS/gkQURE6HFVeP7Y5oJwcQyJgkCbh1el9EOfgzSqSXE3cC/HZQy8i7BKyyhBsn9RYdg07hpcXb4WzXE7aktqKjCGONb4GYHsMgWbi4jkgv4VrTXHFODO3TWnQMOo03v9yLxFHXAhE6GR8/YCwkm0N0DDoHph01jnJYceu0vjDwazxFsMQ4ByaO6ASHnTcERNQ4iyzjyovZuoSMaXT/tkiM4youIj2dOLBl5EGt37JYZKR2S+JZNwZVWePHjv1lSBx5tegowjQbcz0kLq4j0lW41rTj444yz7oxrK83HoInICEu9Xeio+hOsjmQOPpa7rYJc6Z+R5IY78SIVPacJOO5YUIvFnciajKH3YJJIzvDFcvVMmQsNquMmVP6cLcNkc7CaWDrt2xWC2ZO7iM6Bp3Cfz/ahuhuA2GNbyE6iu5sLdojuttASBF+HgKR3sK5psVE2XDp4PaiY9BpvPXVPiSOjrxdNwmDJ0GSuVg83Jn6pzbKYcXMyX2wPu0IAqox+2JS5GnTIhYjzm8Dm5UvoETUdLIs4bpx3fHyJ2mioxDVmTC8E89qIxJg//79mDRpEgDg0KFDdR8DQE5OjqhYTSLLErq1d6FXp2bYdaCk8T9Auios82D/kQq0GHEFile+IjqOrpLG3QTJYhMdgyjihHNNi3JYccOEXvjul1x4fQHRcagBX/10EH++rAvi+l2Eym3fio6jC9kZA9eFPNvGDEw9cQPUHhh26ZD2+GLDQdFRiAAAN0/tAyt32xDRGbJbLbh4UHssXp2FwlK36DhEiHZace2l3eHkbhsi3b322muiI5wTh82Cm6f2xV1z14iOQg14/uMd+O/fRqP0+/eh1lSIjqMLZ7tecLTuyjZpRAKEe02zWmVMv6grPvh6j+godAoLv9qPW8Zfi8q07wDV/BNsruFXABIX15mB6e+0oxxW/PHyXli9ORdev/l/OcnYurdPRO/OzWGx8IaAiM6cRZbw54m98fQ7m0VHIcI1Y8+DxcKFCEQiDB48+JRf+/HHH3VMcnYkSULbFrEY1DMZm3YXiI5Dv3EwrwJ5R6vgGjoFJavfER1HF0mXzeTKZCJBwr2mOe1WTL+oKz7/8QAqqn2i41ADvtiQjRvGdUZc34tQuX2V6DghZYlPQvwFl0G22UVHoSCIiNFjq1XG1NFdRMcgwuwr+rGlDBGdNatFxqBerdCxdbzoKBThmsU7cfmFneGwmX4NEJEhpaen45prrsGsWbNQUlLbbuzIkSP4y1/+gtmzZwtO1zROhxV3XN0fDjvfGxvRvE93If6CyyDZo0RHCbnY3qNgdSWLjkEUscxQ02RZwh8v7yk6Bp3G21/vR+JF1wEmP/elxeWzTP89RpKImLhx2q24akw3pCTFiI5CEWxEagpSWsSG9cF7RCSezSrj3usHQmbLRRLo1ml9wW4yROI8+uijuPTSS9G2bVvMnz8f3377LSZPngy3241ly5aJjtdkUQ4LB7oMauf+YpRUehE/cLzoKCElO2PQnLttiIQyQ02z2yy4aEA7dG+fKDoKncLK9dnwalbE9b1IdJSQiep8PpztekK2cHGdWUiapmmiQ+hBVVVk51XirrnfQ42I75iMxBXrwKv/GINoJw+7JKJz5/EqWLw6C4u+zRQdhSLQ0D6t8PfrLuDZNkQCXXbZZfjyyy8RCAQwbtw4eDwe/OMf/8CECRNERztjXp+Ce+etw/7D5aKj0G8M69sK913TB4demAlNMWf7nxaT/oKYnsPZUoZIIDPVtIKSGsx6ahWUgCo6CjVg4ohOuGlsOxx68VbTnXUjWe1od9vLsMY1Pnm4fPlyzJ8/H4qi4IYbbsCMGTN0SEhnI2LWSsqyjJSkGEwexZZppL+7ru0Pm5VbFYkoOJyO2p2k7ZPjREehCBMfY8ffrhnASRsiwaKiattXWSwWeL1eLFiwICwHuADAZrXg7hkXgBtJjWfDjnxUewOITb1YdJSQcLbriZieFzZp0mb58uW4/PLLcemll+K9997TIR1R5DBTTUuIteO6cd1Fx6BTWLHuAHyaDbF9RomOEnSJF10H2Rnd6PMKCgowd+5cvP/++1i6dCkWLVqEvXv36pCQzkbETNwAtQNdMy7rgdZsmUY6umhAW/Tq1Bw2a0T9uhFRiNmsFtz7R7ZMI3397Zr+cNhYz4hEO7FpQmJiInr16iUwzbmRZQlJrihMHskFdkb0zjcHkDjiKkAy12u/ZLWj5dS7INscjT6Xg1xEoWWmmua0WzF5ZBeeSWpg7/5/9u47PKoyYf/4fc6cKemNFHrvVZqAFEVBRbA3FF3dV9a267qv/bX3LaiL7q6677q2nyi6VtYuCsqCAipK7xBaQgghhWTKmZnfHxFeWV0JkOScTL6f69rFSWaSG+TyyTz3U2ZvVPaxFybUuObL76D0gePrNKbNnz9fw4YNU2ZmppKTk3XiiSfqvffea4SUOByJ87e0jryWqZsuGiyuGUFjyE4P6Mqz+rEyGUC9M01D+VnJOuu4Lk5HQTMxckAr9evcgh2kgAvEYjGVl5drz549krT/n/f9r6lJ8lu68OQeys1KcjoK/s17CzYpIkupvY5xOkq9ql2ZXLcFnUxyAQ0r0cY07iR1t1mfbVDYSJxdN4blU/7ZN8qw6nY1w86dO5Wbm7v/cV5enoqLixsqHo5Qs5tN9pimWuWmatLITnrrsw1Ox0GCu/7CQfJ5meAC0DACfkvnndBNC5bu0NadVU7HQQLLTPPrV+cMYCEC4BJr1qzRsGHD9q9SPvroo/d/zjAMrVy50qloh83ymLr1kqH67+mfKsalpK7y6mdbdN6YyapaPk9S0/93k9ShX51XJks/Psn17bffNlQ8oNlJtDHNNA3lZibpzGO76B8fr3U6Dn7EjI826ZLjL1TVsk+leNO+jyjnxP+SJyVTRh13EMViMRnf280Qj8cPeAx3aZbvvpP8li6a0FMLVxSpqLTa6ThIUOOGtlPXtpmyPM1uYxuARuS1PLrp4iH69UOfiHkuNJT/njyQnTaAi6xatcrpCPXO8phqnZeqS07pqb/PWuF0HHzPzI/W6NxjT1By10GqXrvY6ThHxJOSobyzrqtzaSMxyQU0tEQc0wJ+S+eP66Yla0q0bmvT2zWU6N78bL0uPKGDUnuPUtWyuU7HOWzJXQcrtdfIQxrTCgoKtHjx/43lJSUlysvLa4h4qAfNdkbZa5n6n0uGyvLwAxfqX25mkqae3peVyQAanGkaKshO1uQTezgdBQnquEFt1KNDNne1AWhwAZ+lCSM6amB3JhDc5t1FRcoac4HTMY6QofyzbpTpDRzSqwoKClRSUrL/MZNcAOrC77N052XDlJZctyOs0LhmfLxJ2cc13btuPGnZyjvt1zJ9hzamjRgxQgsWLNDu3btVU1OjDz74QKNHJ8axcYmoaf7trAce01TLFin61bkDnI6CBOOzTN01dRgTXAAaTcBv6YwxnXV07wKnoyDBdGiZrqvO6q8kFiIAaCR+n6UbLxqs7PRDm4hAw3pm1jJ5MvIUaNd0Lw3PHHm2fPkdZHgObUxjkgvA4UpJsnTLJUO5Z9uF3pi7XhHTr9TeI52OchgM5Z91g2T5DvmV+fn5+s1vfqOLL75Yp59+uiZOnKh+/fo1QEbUByO+7xDJZioYtvXc2ys0a95Gp6MgQdx66VAd1T1Pfu62AdDIakK2rn/0UxUWVTodBQkgI9WnP10/VhmpPo6EAdCo7GhMm7ZX6LpHue/GTX4z+SgNz9urHc/f5nSUQ+Zv3V0tL7zzkI6T+b5Zs2bpySefVCQS0dlnn62pU6fWc0IAiSoYsvXGp+v1wnuJdyRcU3fGsZ110ZiW2vKnK5rUXTdZx12ojMETDnm3DZqeZr8lIOCz9LNTeqtv5xZOR0ECmDy+uwZ0zaW0AeAIv9eje38xQqlJbMfHkbE8pu6eOlwpSV5KGwCNzvKYapNfe98N3OPxV5fKV9BRvoKOTkc5JJ60bBWcd8thlzaSNGnSJP3zn//U+++/T2kD4JDsOx3hqG65TkfBv3l9znpFPX6l9jrG6Sh1ltJrJKVNM9LsixtJ8vs8uvXnQ5Wfnex0FDRhw/q01FnHdeFeGwCOMU1DaSle3XHZ0TJNJttx+K49/yi1yUvl2E8Ajgn4LJ08oqNGH9Xa6Sj4TjBs66u1u5U1+nyno9SZ4Quo5ZS7Zfp4rw/AOX6fpZt/NkS5mUlOR8G/eemTzco6bkqTuOvG36qLck+5ktKmGXH/38pGEvB5dO/lIxTwsVMCh65jq3Rdd+FA+X2UNgCc5bU86tgqQ5ef3tfpKGiizji2i47uXcCYBsBxAZ+la84doJ4dsp2Ogu889sq3SurQV1ZWS6ejHJxhquCcm2WltZDh4X0+AGf5vR7dd+UI7o50mVc/WaeoFVBKzxFOR/lJnrRsFZx/G6VNM0Nx8x2PaSonI6CbLh7CpWE4JJmpft1z+QiORwPgGgGfpbFD2uqEIW2djoImZlCPPF14Ynd2jwJwDb/P0p1Th6llTorTUSCprDKkVYXlyhp1jtNRDqrFiZfJ36qrTO+hX94MAPXN4zHVIiNJ9/xiuCwPE49u8vKcQmWPde+uG8PyqeUFd8rwsWOruXHn30iH+Lwe9emUo0tO6eV0FDQRlsfU3b8YrtQAdwAAcJeAz9IVZ/ZT7045TkdBE9EmL1U3XTyEnTYAXCfJ59Fvrx6pzNTDv6ME9Wf6y98opcdwedLcuxMqffAEpfYdw8pkAK7i83rUsVW6rr9wEIvGXeSVj9cqaiUrpedwp6P8kOlRwbm3yMrIlenhfVpzQ3HzbwJ+SxNGdNS5x3d1OgpczmMauu3nQ9UqN0UWdwAAcCG/z9Kdlw1Tt3ZZTkeBy+VmJenBq0eyexSAK5mmqbQUrx68+hiOmHGB7buqVVhcqczhZzgd5Uel9Bqp7LFTKG0AuJLfZ2lQz3xdcWY/p6Pge16ZW6js46ZIclGjZpjKP+sG+dt0l+ll8UpzxGzzjwj4LZ1zQjedOqqT01HgUqZp6JZLhqh3pxwFWJkMwMWS/JbuvXy4OrZKdzoKXConI6Bp14xWWrJXpumiNyoA8D1ey6O8rGTde/lwSmYXePQfy5Q24HiZSalORzlASo8Ryp14FRNcAFwt4LM0dlBbTTm5h9NR8J2XZ69RzJviol03hvJO/7WSOvRlTGvGPHfdddddTodwI8tjqk+nHJXvDWv91nKn48BFTEO66eIhOqp7HqUNgCbB8pgac1QbLVxepPK9YafjwEWy0wN66NrRykz1y+NhPQ8Ad/N4TKUl+zS4Z74+W7JNdjTmdKRma3dFUMcPaqWUgKXg5mVOx5EkJXcfqrzTrmGCC0CTYFmmurTJVDQa18pNu52OA0mmZWnwqGGqWPSO01HU4pSrlNJ9GLtHmzneof8Ev8/SZaf10cnDOzgdBS5hmoZuuGiwBlLaAGhCDMNQkt/S7341Sh1asvMGtbLTA5p2zShKGwBNit/nUYeW6frdL0cqJcDP4056/I1VyhgyUYbX+Uml5K6DlXfatZQ2AJqUgM/S5BO768KT2HnjBi99uEYxX4pSegxzNEf2+J8rtdcxlDZgx83BWB5Tfbu0UDBsa03hHqfjwEGWx9D/XDK0dqcNZ2sDaGIMw5DXMnXsoDb6evVOlVWGnI4EB+VlJemha8coM80vi9IGQBPj8ZhKSfLqmH6t9OnXWxWOsPPGCTtK92rCsLbyxcMKbVvjWI6kLgOVf+Z1lDYAmiTLU7vzpkVGQF+u2ul0nGbP0V03hqkWp1yptL5jKG0giR03dRLwWbp4Qi+ddVwXp6PAIV7L1J2XDVf/ri3YaQOgyTIMQ8kBrx646hh1bZvpdBw4pFWLFD187RhlpPoobQA0WT7Lo/ycZD187RhlpjJh75Sn3lmrzJFnSR5n3iOl9hur/DOvp7QB0KQF/JbGDm6n6y8cxJ2TDnvpwzWK+VOV0v3oxv3GHkv559zMThscgB03dWR5TPXokK2c9IC+WlOieNzpRGgsyQFL9/5iuLq1y5Sf0gZAAvBaHo0Z2EaFRZXaVlLldBw0os6tM/S7X45UapJPHpPSBkDT5jFN+X21Y9q8b7arJmQ7HanZ2VxUqdNHdZRZU65w8cZG/d5Zo89X9rGTKW0AJATLMpWfk6xeHbM175vtijHx6BjL69XAUUerYtG7jfL9DF+SWk25W4HW3ShtcACKm0NgeUy1y0/TwO65WrB0hyI2W/ITXevcVE27ZpRatkiltAGQUCyPqaN7F8g0DS3bUOp0HDSC0Ue11q2XDlWS32IlH4CE4TFNBXwejTu6vZauL1VpedDpSM1OJGZq+LHDVL7obUmNMNFomMo99VdK6z+WCS4ACcXymMpJT9LAHnma98122VHmHZ2wdH2pzh3XU9Gy7YqUbmvQ7+VJyVCrnz0gb05rFiLgByhuDpFlmcpM9Wvs4LZauKJYVdURpyOhgQzqkad7rxihtGSfLItVyQASj+Ux1a1tlrq2zdIXy3YoGmNVVyIyDenSSb114Uk9FPBZMgxKGwCJxTQN+b0ejRnYWrvLg9q4vcLpSM3K6sIynXN8N8X27FBk19YG/V6GN6CWk29TUod+lDYAEpLlMZWe4tPYwW21eGWxKpl3dITX79PAY4aqYnHD7brx5rZTq589ICstW6blbbDvg6aL4uYweDymkvwenTC0ndZu2aPi3dVOR0I9O/f4rrrizH4K+JngApDYLMtUXlaSRg5orc+XFXHMTIJJDli6a+pwHd27QAE/O0cBJDbLY2pA91xlpvm1ZPXOxtj7ge/4A34dNXxQg05wWZn5avWz++Vr0Vamj1XJABKX5TGV7Lc07uj22rSjQttL9jodqdlZum6XzhvfU3bZtgbZdZPSa6QKzr1ZZiBVhump96+PxEBxc5gMw5DX8uiYfq1UE45oTeEepyOhHvi9Ht188RAdP6QdE1wAmg3LYyolyatxQ9tr6bpd2l3BMTOJYN9xn63zOO4TQPNheUy1L0jXUd3z9DnHWzeaZRt26bzxvRUp3ii7rKjev35y96FqecEd8iRnyLQY0wAkvtp5R1PD+hTI77e0dN0upyM1O/6AX0eNGKqKxe/U3xc1TOWc+HNljTpXpi/AYnH8JIqbI2R5TPXulKPWualavLJYnDLTdOVmJul3vxqpzm0yKW0ANDumaey/4HlnWbU276h0OhKOAMd9AmjOLMtUZppfxw9pp69X71T53rDTkRJePC7lZKWq54A+qlzyYf19YdOj7HGXKvvYC5jgAtAsWR5TnVtnqH/XXH2xjAUJjenbdbt03ok9ZZduVaR0+xF/PTM5XS2n3KXkjgM47hN1QnFTDyyPqVa5KRo7uK2WrS/VnqqQ05FwiIb0ytc9l49QVppfXi9bFAE0X5bH1MAeeerUKkNL1pbwxqCJsTyGLjy5py47tQ/HfQJo1jweUwGfpXFD2ytsR7W6sMzpSAnvm7UlOv+UAQpuXqZoZekRfz1PWrZaTblbyR37M8EFoFmzLFNZ6QGdMLSdlq7bpbJK5h0bS1LArwHDhxzxUaCBDn3Vaso98mbkyvRy3CfqxojH4+wRqSexWFwRO6bX5qzTzA9Xc8lzE5CW7NUvzxmggT3yFOAYGQDYLxyJKhiO6uEZX+rLVTudjoM66Nw6QzddPERZ6X7GNAD4npqQrcKiCv3uucUq2VPjdJyEdtNFgzQwo0xFM+46oq+T0mOYWpxylQyvX6aHMQ0AJCkejysciWrWvA164b1VsqPMOzY0w5D+ce847Z41XdVrFx/66y2fcsb/XKl9RlPY4JBR3DSAYNjWrj01evDZRSos4qgZtxrWp6V+ff4A+bwe+Sx22QDAjwmGbX2+dIcef+1bVQdtp+PgR1geU1NO6qGJIzvJ5zXZZQMAP8KOxhSxY3r81W/0yZdbnY6TsFKTvHrhjuO17ZmbFCnZcsiv96RkKHfiLxVo14tdNgDwHwTDtsoqQvrdc4u0flu503ES3s9O6aVT+ydr6xPXHNLr/K26Kv+sG2QmpVLa4LBQ3DSQ2t2gJC0ZAAAgAElEQVQ3Ub0ye61e+XitYuy+cY30FJ+uOXeA+nfN5S4bAKiDUCSqYMjWH/7fl/pmbYnTcfA9Xdtm6qaLBysjlV02AFAXwZCtZRtK9ciLX6mCu28axD1Tj1bX+EbtfG3aIb0utfdotTh5qgyPV4blbaB0AJAYanffxPTmZ+v14vvsvmlIpim9cs847X7rj6pe92UdXmApe8xkpQ85mcIGR4TipoEFQ7aKy6r122cXaevOKqfjNHvH9GulX507QD6vKS+7bADgkITCtj5bsl1Pvv6tguGo03GaNa9l6uIJPXXy8I7ssgGAQxSJRBWJxvT3Wcv1wRebxTvi+tUiM6Cnbj5OW5/8tezygx+36knLVu6kXynQuhu7bADgEAXDtnZXBPX75xaz+6YBXTqxlyb2TdbWJ396101SpwHKPeUqmYEUxjQcMYqbRhCLxRSx4/po4WbN+GA1K7sc0LJFii4/o696d8xhlw0AHIFQxFY4EtMz/1yujxZtYUepAwb1yNPVZ/dXWoqPXTYAcARqQrZKyqr1x5e+1tote5yOk1Ae/tUI5e/5Rrvefvw/Psfw+pU54kxlHD1JhumRwV02AHBY9t25/a9vt+nvs5arvIp5x/pmmtI/7hmnXW89opp1X/3g81ZWgVqcfDmLEFCvKG4aUTgSVSwW16ufrNXrc9crxGrlBpedHtDPTumpY/q3lmUa8nhMpyMBQEKoCdmqrA7rr68v1Rf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      "text/plain": [
       "<Figure size 2160x1440 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(4,4,figsize = (30,20))\n",
    "axx = ax.flatten()\n",
    "\n",
    "index = 0\n",
    "for column in cat_ls:\n",
    "    # train[column].value_counts().plot(kind='pie', ax = axx[index], title=column, autopct='%.0f', fontsize=12)\n",
    "    train[column].value_counts().plot.pie(autopct = '%1.0f%%', title='Train '+column, ax = axx[index])\n",
    "    index+=1\n",
    "    test[column].value_counts().plot.pie(autopct = '%1.0f%%', title='Test '+column, ax = axx[index])\n",
    "    index+=1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Bar plots for categorical variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x1440 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(2,4,figsize = (30,20))\n",
    "axx = ax.flatten()\n",
    "\n",
    "index = 0\n",
    "for column in cat_ls:\n",
    "    # train[column].value_counts().plot(kind='pie', ax = axx[index], title=column, autopct='%.0f', fontsize=12)\n",
    "    train[column].value_counts().plot.bar( ax = axx[index])\n",
    "    index+=1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Insights:\n",
    "\n",
    "* The distribution of every variable is same in both train and test data.\n",
    "* Most of the houses are posted by Dealer (62%). Very few (2%) are posted by Builders.\n",
    "* Only 18% of Houses are Under Construction.\n",
    "* Most of the houses (45%) have 2 rooms. followed by 3, 1 and 4. \n",
    "* Almost all the houses are BHK."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Kdeplots, Distplot, Boxplot for Numerical Variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_ls = ['SQUARE_FT']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ujBGR33E4HOjr68O///4rta1duxY6nQ6tra1oamrC119/jaCgIACARqNBRkYGfvrpJ5SVlSEjI8PjY5WVleGBBx5AaGgoDhw4MKEwG0sIAZvNhpCQEO+DIyIiIpIh1l9EJFdcGCMivxMSEoLt27fj2Wefxa233orY2FgkJiYiLS0NFRUVuOeee6SibKz77rsP9fX1Hh/HbrfDarWiqqoKoaGhePfdd/Hnn38iOjpa+s6rr74KrVYLu90OAFi5ciX27dsnfT4wMIB169aN229sbCx27tz5f49vtVrR0tIibRsMBrz44osenz8RERHRdGH9RURyxYUxIvJLW7ZsweOPP46mpiY0NTVh//792L9/P9LT0//z/wkhAGDcsyrGcrlcmDVrFgDgs88+Q3R0tPQMieTkZBw8eBBvvvmm9P2rv8p//vx5bNmyBUuWLEFUVJT0+Y34VX4iIiKimcD6i4jkiG+lJCK/09LSgg8//BA6nQ6rV69Gdna29GBWrVaL33//HQ6HA8Do8zB6enoAAI2NjVi2bBkAIDQ0VPop41X9/f0YHBzE3LlzIYRAeXk5/v77b6SkpCAlJQWtra2wWCzS/saKiopCQUEB3nnnHfz22283OANERERENxfrLyKSKy6MEZHfCQsLw/vvv4/m5map7dKlS+jv78eDDz6IxMRE5OTk4MqVKzh//jw2bdqEl156CWfOnMGmTZsAAHq9HidOnEBHRweA0Z9kHjhwAPHx8ZgzZw7q6+tx+fJlfPPNN6itrUVtbS3q6uoQHh6OiooKt+cVGxuL9evX44033oDL5brxiSAiIiK6SVh/EZFc8U8picjvLFq0CMXFxSgqKsLFixeh1WoRHByM/Px8LF68GIWFhSgpKcHmzZsBAENDQ5g1axbmzJmDmpoabNiwAStWrEBGRgaee+45AKPPorjrrruk122XlZXhiSeeQHBwsHRctVqNzMxMmM3mCa8Zv2rbtm1ITU1FZWUlVq5c6fYZFwCwe/duLFmyZLpTQ0RERHRDsP4iIrlSiat/sE1ERP+pt7cXra2tSE5OnulTISIiIvILrL+I6EbjwhgRkQI1NjZi165dbj9LTExEbm7uTT4jIiIiIt/G+ovIN3FhjIiIiIiIiIiI/BIfvk9ERERERERERH6JC2NEREREREREROSXuDBGRERERERERER+iQtjRERERERERETkl7gwRkREREREREREful/SPlQ3mZAPPIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(2, 2, figsize=(20, 10))\n",
    "axx = ax.flatten()\n",
    "\n",
    "\n",
    "sns.kdeplot(train['SQUARE_FT'], ax = axx[0])\n",
    "axx[0].ticklabel_format(style = 'plain')\n",
    "sns.kdeplot(test['SQUARE_FT'], ax = axx[1])\n",
    "axx[1].ticklabel_format(style = 'plain')\n",
    "sns.boxplot(train['SQUARE_FT'], ax = axx[2])\n",
    "axx[2].ticklabel_format(style = 'plain', axis = 'x')\n",
    "sns.boxplot(test['SQUARE_FT'], ax = axx[3])\n",
    "axx[3].ticklabel_format(style = 'plain', axis = 'x')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Square_ft is highly left skewed. \n",
    "* Almost all the houses have Square_ft below 400000."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# Bivariate Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Boxplots for categorical Variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x1440 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(3,3,figsize = (30,20))\n",
    "axx = ax.flatten()\n",
    "\n",
    "for index, column in enumerate(cat_ls):\n",
    "    sns.boxplot(data = train, x = column, y = target, ax = axx[index])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Scatterplot for Numerical Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1ef2ea3da88>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.ticklabel_format(style = 'plain')\n",
    "sns.scatterplot(data = train, x = 'SQUARE_FT', y = target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x125a3264c88>"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1620x1620 with 90 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(data = train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# Hypothesis Testing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Does house price is more when dealer is posting?\n",
    "2. Does Under_Construction houses have less price?\n",
    "3. Does RERA approved houses have more price?\n",
    "4. Houses with greater number of rooms have more price.\n",
    "5. Higher the square_ft higher the price.\n",
    "6. Resale 1 have perticularly less price.\n",
    "7. What are the cities with higher price rate."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Does house price is more when dealer is posting?\n",
    "\n",
    "We will see Median price of Owner, Dealer and Builder. We are choosing median becuase it's less affected by Outliers since our data has so much outliers.\n",
    "\n",
    "Answer:\n",
    "\n",
    "    Yes. House's price is way higher when dealer is posting it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x125a72d3ac8>"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train.groupby('POSTED_BY')[target].median().plot(kind = 'barh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Does Under_Construction houses have less price?\n",
    "\n",
    "Answer:\n",
    "\n",
    "    Yes. Under_Construction houses have slightly less price."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x125a73f7048>"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train.groupby('UNDER_CONSTRUCTION')[target].median().plot(kind = 'barh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Does RERA approved houses have Higher price?\n",
    "\n",
    "Answer:\n",
    "    \n",
    "    Yes. RERA approved houses have Higher price than those who do no thave."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x125a7442088>"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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1a9Zo0aJFam1t1ZgxY1RYWBjvSZL+iOeBAwc0c+ZMhcNhzZkzR+PHj/fl99m4ceP0yCOPaM6cOerq6tI999yj2bNn66abbvLlMdDQ0KC0tLTIbb+2oAfvMAUAxvnm1A0AwBuEHgCMI/QAYByhBwDjCD0AGEfoAcA4Qg8AxhF6ADDufwDE8f7kBDwW1gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train.groupby('RERA')[target].median().plot(kind = 'barh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. Houses with greater number of rooms have more price.\n",
    "\n",
    "Answer:\n",
    "    \n",
    "    Yes. But its not the case for all the room_numbers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x125a88aa848>"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train.groupby('BHK_NO.')[target].median().plot(kind = 'barh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5. Higher the square_ft higher the price.\n",
    "\n",
    "Answer: \n",
    "    \n",
    "    Yes. As the square feet increases the price is also increases. But its not the case for every time (Specially Square feet <50000)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x125a49cd688>"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.ticklabel_format(style = 'plain')\n",
    "sns.scatterplot(data = train[ train['SQUARE_FT']<500000], x = 'SQUARE_FT', y = target)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6. Resale 1 have perticularly less price.\n",
    "\n",
    "Answer: \n",
    "    \n",
    "    Yes. Resale 1 have slightly less price than Resale 0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x125a1fa2b08>"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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aN2+eHnjgAb366qvq1auX9u7dK0kqLi6OyNklqbGxUStWrFBra6uampr06aef6rXXXouK129qaqq+//57NTQ0qL29Xd99950mT54cFfvNJYcOHdIdd9yh+Ph4SZ173UbMEX///v1VUFCg3NxctbW1KTs7W8OGDQv3WB3Sq1cvLVu2TE8//bRaW1s1ceJETZ48OdxjXdV7772n1tbWwFGDJOXk5ETN/BMnTtSBAwc0ffp09ejRQ2lpafJ6vUpISIiK+a9m5cqVWrRokZqamjR06FDl5uaGe6SrSk1NVWVlpaZPny6/36/Zs2dr5MiRUfH6HT58uObOnavZs2erra1N48aN06xZszRo0KCo2W9qamqUnJwcuN+Z7vAXuADAmIg51QMA6B6EHwCMIfwAYAzhBwBjCD8AGEP4AcAYwg8AxhB+ADDmv3sIWqPg09Q0AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train.groupby('RESALE')[target].median().plot(kind = 'barh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7. What are the cities with higher price rate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "train['City'] = train['ADDRESS'].apply(lambda x : x.split(',')[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "City\n",
       "Cuddalore      650.00\n",
       "Vidisha        320.00\n",
       "Gurgaon        140.00\n",
       "Hathras        140.00\n",
       "Maharashtra    130.00\n",
       "Nizamabad      120.00\n",
       "Mumbai         120.00\n",
       "Lalitpur       110.00\n",
       "Srinagar        90.00\n",
       "Hassan          90.00\n",
       "Arrah           85.50\n",
       "Bhadrak         85.00\n",
       "Idukki          84.50\n",
       "Panaji          82.50\n",
       "Jammu           80.00\n",
       "Sagar           80.00\n",
       "Bangalore       77.75\n",
       "Faizabad        75.00\n",
       "Kottayam        72.75\n",
       "Ludhiana        72.00\n",
       "Phagwara        70.00\n",
       "Noida           70.00\n",
       "Salem           69.00\n",
       "Erode           68.00\n",
       "Panchkula       67.50\n",
       "Kochi           67.00\n",
       "Pune            67.00\n",
       "Kollam          66.50\n",
       "Karwar          64.50\n",
       "Dehradun        63.20\n",
       "Name: TARGET(PRICE_IN_LACS), dtype: float64"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.groupby('City')['TARGET(PRICE_IN_LACS)'].median().sort_values(ascending = False)[:30]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
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 },
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